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# 36. Discourse relations and coherence

**On this page**

1. [1. Cohesion and coherence](#1-cohesion-and-coherence)
2. [2. Coherence relations: the families](#2-coherence-relations-the-families)
3. [3. The frameworks and the French resources](#3-the-frameworks-and-the-french-resources)
4. [4. LEXCONN: the relations of French connectives](#4-lexconn-the-relations-of-french-connectives)
5. [5. French connectives and their syntax](#5-french-connectives-and-their-syntax)
6. [6. Cause: *car*, *parce que*, *puisque*, *comme*](#6-cause-car-parce-que-puisque-comme)
7. [7. Contrast and concession](#7-contrast-and-concession)
8. [8. Time and narrative](#8-time-and-narrative)
9. [9. Implicit relations](#9-implicit-relations)
10. [10. Questions under discussion](#10-questions-under-discussion)
11. [11. Segmentation and parsing for French](#11-segmentation-and-parsing-for-french)
12. [12. How Mova handles it](#12-how-mova-handles-it)
13. [In Mova](#in-mova)
14. [Sources](#sources)

A French text holds together when its parts are related: one sentence gives the cause of another (*car*, *parce que*, *puisque*), contrasts with it (*mais*, *alors que*, *en revanche*), concedes something against it (*pourtant*, *bien que*), follows it in time (*puis*, *ensuite*), or rephrases and sums it up (*c'est-à-dire*, *bref*, *enfin*). This chapter describes how French signals these relations: its connectives and their syntax in the UD trees, the order of clauses, the narrative tenses, and the questions a text answers. It also covers the frameworks and resources that annotate French discourse: SDRT in ANNODIS, a PDTB-style French Discourse Treebank, the LEXCONN lexicon of connectives, RST in translation, and DiscoGeM for implicit relations. It ends with what Mova's frame reader and QUD stack do with discourse structure: for English, a little; for French, nothing yet. Every count is on the UD 2.18 French treebanks and was made on 2026-11-06.

Contents

1. [Cohesion and coherence](#1-cohesion-and-coherence)
2. [Coherence relations: the families](#2-coherence-relations-the-families)
3. [The frameworks and the French resources](#3-the-frameworks-and-the-french-resources)
4. [LEXCONN: the relations of French connectives](#4-lexconn-the-relations-of-french-connectives)
5. [French connectives and their syntax](#5-french-connectives-and-their-syntax)
6. [Cause: *car*, *parce que*, *puisque*, *comme*](#6-cause-car-parce-que-puisque-comme)
7. [Contrast and concession](#7-contrast-and-concession)
8. [Time and narrative](#8-time-and-narrative)
9. [Implicit relations](#9-implicit-relations)
10. [Questions under discussion](#10-questions-under-discussion)
11. [Segmentation and parsing for French](#11-segmentation-and-parsing-for-french)
12. [How Mova handles it](#12-how-mova-handles-it)

---

## 1. Cohesion and coherence

**Cohesion** (*cohésion*) is the set of surface ties between sentences: reference by pronouns and definite noun phrases (*il*, *celle-ci*, *ce dernier*, *le directeur*; [chapter 35](https://md.mova.elamur.ai/free/en/docs/languages/fr/35-reference-and-coreference/)), ellipsis, connectives, and lexical repetition. **Coherence** (*cohérence*) is the relation a reader infers between the meanings. The two come apart. A text can be cohesive and still make no sense, and a text can be coherent with no tie at all: *Ne sors pas. Il pleut.* "Don't go out. It's raining." is read as a reason without any *car*. The English chapter gives the classic inventory, Halliday & Hasan's *Cohesion in English* (1976; not open). French linguistics follows the same split, usually in the terms of the French discourse tradition (the *linguistique textuelle* of the 1970s–1990s; not open, *Wanted*).

French expresses relations with a large closed class of connectives, and most of them are multiword. Brunot (1899, *Précis de grammaire historique*, `brunot-1899`, ch. on invariable words) notes that French kept few of the Latin particles. It rebuilt its adverbs, prepositions and conjunctions by putting words side by side: *à cause de*, *désormais*, *toujours*. The connectives show the same history (*parce que*, *bien que*, *alors que*, *en effet*, *par conséquent*, *c'est-à-dire*). Clédat (1894, *Grammaire raisonnée*, `cledat-1894`) gives the Latin source of *car*, *quare* "for which reason", a source it shares with no other French conjunction. The multiword form matters for parsing: a UD tree must decide whether *en effet* is one fixed word or a preposition with its noun (§5).

## 2. Coherence relations: the families

Every framework cuts the relations differently, but the same five families recur (Hobbs, Kehler, RST, PDTB and SDRT; the English chapter [36 §2](https://md.mova.elamur.ai/free/en/docs/languages/en/36-discourse-relations/#2-coherence-relations-the-families) has the references):

| family | relations | French signals | example |
| --- | --- | --- | --- |
| causal | cause, result, reason, purpose, condition, explanation, justification | *car, parce que, puisque, comme, donc, alors, c'est pourquoi, si, pour que, afin de* | *Il purifie tout **car** il supprime les odeurs.* |
| temporal | narration, sequence, simultaneity, flashback | *puis, ensuite, alors, après, avant que, quand, lorsque, pendant que, dès que* | *Il est aboli, **puis** restauré.* |
| contrast and concession | contrast, opposition, concession | *mais, or, alors que, tandis que, cependant, pourtant, toutefois, néanmoins, en revanche, par contre, bien que, même si* | ***En revanche**, cette voie est hors de portée.* |
| expansion | elaboration, instance, rephrasing, continuation, alternation, summary | *et, ou, en effet, par exemple, c'est-à-dire, de plus, en outre, enfin, bref, en fait* | ***En effet**, la jeune université compte 100 étudiants.* |
| attribution and metatalk | reported speech, evaluation, digression, detachment | *dire, selon, d'après*; *à propos, au fait, de toute façon, quoi qu'il en soit* | ***Selon** des chercheurs…* |

The examples are from GSD (§5, §7). The last family holds the relations that link speech acts rather than facts. They are the "metatalk" relations of SDRT and LEXCONN (§4), and they are where *puisque* and *de toute façon* do most of their work.

## 3. The frameworks and the French resources

The three frameworks of the English chapter, RST, PDTB and SDRT, all have French applications. A fourth line of work starts from the connectives themselves.

**SDRT: ANNODIS.** SDRT (Asher & Lascarides 2003; not open) builds a graph of discourse units joined by relations that are either coordinating (Narration, Continuation, Contrast) or subordinating (Elaboration, Explanation, Background). New material may attach only on the *right frontier*. The main French corpus is **ANNODIS** (Afantenos et al. 2012, `afantenos-2012-empirical-resource-discovering-cognitive-principles`; Péry-Woodley et al. 2009, 2011, `woodley-2009-annodis-une-approche-outillee-de`, `woodley-2011-le-corpus-annodis-un-corpus`). It annotates texts of several genres in two ways: as a bottom-up SDRT structure over elementary discourse units (EDUs), and as a selective top-down annotation of larger structures such as enumerations. **EXPLICADIS** (Atallah 2015, `atallah-2015-la-ressource-explicadis-un-corpus`) adds a finer annotation of causal relations to ANNODIS-style texts.

**PDTB: the French Discourse Treebank.** The **FDTB** (Danlos et al. 2012, `danlos-2012-vers-le-fdtb-french-discourse`; Danlos, Colinet & Steinlin 2015, `danlos-2015-fdtb1-premiere-etape-projet-french`) applies the PDTB method to the French Treebank, a corpus of *Le Monde*. Its first stage, FDTB1, identified more than ten thousand connective occurrences and told them apart from non-discourse uses of the same words. The hard cases were *ainsi* as a manner adverb and prepositions that head complements: of 1 161 occurrences of *pour* + infinitive, 518 (44%) were purpose connectives.

**RST in translation.** No open native French RST treebank is in the research library. Pastor, Marino & Oostdijk (2024, `pastor-2024-la-reconnaissance-automatique-des-relations`) translated the English RST-DT test set (38 documents, 2 308 EDUs) into French one EDU at a time and ran the multilingual DMRST parser on it. Relation classification scored F1 0.54, against 0.65 on the English original, which is near the published scores for Spanish (0.63) and Portuguese (0.62). In their error analysis *si* was a reliable cue (73% of 41 conditions recognised), while *et* occurred in Joint, Temporal and other relations and misled the parser.

**Lexicons and classifiers of connectives.** **LEXCONN** (Roze, Danlos & Muller 2012, `roze-2012-lexconn-french-lexicon-discourse-connectives`) lists French connectives with their syntactic category and SDRT relations (§4). Laali & Kosseim (2017, `laali-2017-automatic-mapping-french-discourse-connectives`) mapped the 371 connectives of LEXCONN v2.1 (on average 1.3 relations each, 37 still unassigned) to PDTB senses. They parsed the English side of Europarl with a PDTB parser and carried the senses across the word alignment. The result, ConcoLeDisCo, holds 900 (connective, relation, probability) triples. Only Concession and Condition are defined alike in both inventories; on those, it recovered 36 of 44 LEXCONN connectives (81%). Rauh, Zaczynska & Bourgonje (2023, `rauh-2023-multilingual-connective-database-aligning-german`) aligned the French and German concessive connectives in the same way. **Relex** (Sow, Toussaint & Constant 2026, `sow-2026-relex-common-denominator-connectives-discourse`) marked connectives in 35 million tokens of French press and online debate with rule-based automata, which agreed with the FDTB at F1 0.76 once ambiguous candidates were set aside. It labelled each *monosemous* connective with its single LEXCONN relation and fine-tuned CamemBERT to predict 19 relations. On connectives unseen in training it reached F1 0.59. In its hand-checked test set, 19 of the 42 cases sent to the expert expressed two relations at once.

**Implicit relations, causality, attribution.** **DiscoGeM 2.0** (Yung et al. 2024, `yung-2024-discogem-2-0-parallel-corpus`) has 12 834 implicit relations in English, German, French and Czech, each labelled by ten crowd workers who inserted a connective, so each relation is a distribution of readings (§9). **FreCaDiS** (Blochowiak et al. 2026, `blochowiak-2026-argumentation-through-discourse-relations-subjectivity`) annotates *parce que* and *car* in five genres, from SMS to fiction, as explanation or justification and as subjective or objective (§6). **FRACAS** (Richard et al. 2024, `richard-2024-fracas-french-annotated-corpus-attribution`) annotates quotations and their sources in 1 676 news texts: the attribution relation ([chapter 38](https://md.mova.elamur.ai/free/en/docs/languages/fr/38-dialogue-and-discourse-markers/)).

| resource | framework | what it annotates | licence of paper / data | in `$MOVA_DATA` (2026-11-06) |
| --- | --- | --- | --- | --- |
| ANNODIS, EXPLICADIS | SDRT | EDUs, relations; causal relations | NC | no |
| FDTB1 | PDTB | connectives of the French Treebank | paper NC-ND; data not checked | no |
| LEXCONN | SDRT relations | 328 connectives (2012) | NC-ND | no |
| ConcoLeDisCo, Relex | PDTB / LEXCONN relations | connective → relation | papers CC BY; data on GitHub, licence not checked | no |
| DiscoGeM 2.0 | PDTB 3 | implicit relations, 4 languages | NC | no |
| FreCaDiS, FRACAS | causal; attribution | *car*/*parce que*; quotations | NC | no |

Papers under NC or ND licences inform this chapter but are not quoted. The open (CC BY) papers are paraphrased with their slugs.

## 4. LEXCONN: the relations of French connectives

LEXCONN 2012 lists **328 connectives with 428 usages**: a connective with two relations has two usages (Roze, Danlos & Muller 2012). The tests for a connective include that it links two discourse segments, that its meaning is not compositional and that it contains no referential expression. The authors found each connective's relations by reading contexts in the Frantext corpus. They also used a substitution test: *dès lors que*, *puisque* and *étant donné que* can replace one another without changing the reading, so they share a usage.

The relations are fifteen of SDRT plus six the authors added because no SDRT relation fitted:

| kind | relations | typical connectives |
| --- | --- | --- |
| temporal | Narration, Background (forward or backward), Flashback | *puis, ensuite*; *alors que* (background); *auparavant* |
| causal | Result, Explanation, Goal | *donc, par conséquent*; *parce que, car*; *pour que, afin de* |
| structural | Parallel, Contrast, Elaboration, Continuation | *de même*; *alors que, tandis que*; *notamment*; *et, de plus* |
| logical | Alternation, Consequence (condition) | *ou, sinon*; *si, à condition que* |
| metatalk | Result*, Explanation* | *donc* on a speech act; *puisque*, *car* justifying an utterance |
| added (not SDRT) | Concession, Opposition, Summary, Detachment, Digression, Rephrasing | *même si, bien que*; *cependant, malgré tout*; *en gros, globalement*; *de toute façon, quoi qu'il en soit*; *à propos, au fait*; *enfin, tout au moins* |

By share of usages, the largest classes are Opposition (9.5%), Result (8.1%), Concession and Continuation (7.4% each), Explanation (6.5%), Goal and Condition (5.8% each), Explanation* (5.6%) and Narration (5.4%). French thus has many connectives for opposing and conceding and for causes, and comparatively few for plain narration, where the order of telling does the work. The added Concession relation answers a real problem. ANNODIS had treated *bien que* and *même si* as markers of the coordinating Contrast. LEXCONN argues from the right frontier that concession is subordinating: a segment after the concessive can still attach to the segment before it.

The starred relations are where French grammar diverges most from a fact-only reading. In *Il est malade, puisqu'il ne vient pas* "He's ill, since he isn't coming", the absence is not the cause of the illness. It is the speaker's evidence for saying so (Explanation*). In *Tu as fini ? Donc on peut partir.* "Have you finished? So we can leave", *donc* introduces a conclusion about what to do, not a result of a fact (Result*). A reader that turns every *puisque* into a `cause` link gets these wrong (§12).

## 5. French connectives and their syntax

As in English, discourse connectives are a functional class, not a part of speech. In UD French they are coordinators, subordinators, adverbs, prepositional phrases and fixed multiword expressions. Their relation in the tree follows their syntax, not their discourse function.

| syntactic type | UPOS | UD relation | examples | Arg2 |
| --- | --- | --- | --- | --- |
| coordinator | CCONJ | `cc` on the second conjunct, which is `conj` | *et, mais, ou, ni, car, or*; *donc* (sometimes) | the second conjunct |
| subordinator | SCONJ (or ADV + `fixed`) | `mark` on the subordinate predicate, which is `advcl` | *parce que, puisque, comme, si, quand, lorsque, bien que, alors que, tandis que* | the subordinate clause |
| adverb | ADV | `advmod` of the clause it modifies | *donc, alors, ainsi, puis, ensuite, cependant, pourtant, toutefois, néanmoins, enfin* | its clause; Arg1 anywhere before |
| prepositional phrase | ADP + NOUN | `obl:mod` (+ `case`), or one `fixed` word | *en effet, par exemple, en revanche, par contre, en fait, de plus* | as adverbs |
| interjection-like use | ADV, INTJ | `discourse` (spoken treebanks) | *donc, enfin, alors, en fait, bon, ben* | none in the tree |

The tree shows the difference between the two causal connectives at once (UD French GSD 2.18):

```
fr-ud-train_02191   Il purifie tout car il supprime les odeurs nauséabondes.
  purifie ─conj→ supprime ─cc→ car            (car: CCONJ, the cause is a conjunct)

fr-ud-train_03202   Le crédit était mort parce que les banques n'avaient plus de liquidités.
  mort ─advcl→ avaient ─mark→ parce ─fixed→ que   (parce que: the cause is an adverbial clause)
```

With *car* the cause is a coordinated main clause; with *parce que* it is a subordinate clause. This is the grammars' classic contrast: *car* cannot be clefted (**c'est car…*) or answer *pourquoi ?*, while *parce que* can. A reader that looks for causes only under `advcl` misses every *car*.

**How the connectives are annotated.** All treebanks, all splits, one count per head word (the fixed parts of a multiword expression are folded into it):

| expression | relations (count) | total |
| --- | --- | --- |
| *mais* | `cc` 1 518 | 1 564 |
| *ou* | `cc` 1 405 | 1 437 |
| *car* | `cc` 182 | 189 |
| *parce que* | `mark` 346 | 357 |
| *puisque* | `mark` 92 | 93 |
| *alors que* | `mark` 155 | 158 |
| *donc* | `advmod` 602, `discourse` 113, `cc` 71 | 800 |
| *alors* | `advmod` 397, `discourse` 68 | 479 |
| *puis* | `cc` 307, `root` 29, `advcl` 9 | 357 |
| *ainsi* | `advmod` 233 | 244 |
| *ensuite* | `advmod` 209 | 212 |
| *cependant* | `advmod` 163 | 163 |
| *enfin* | `discourse` 228, `advmod` 74 | 309 |
| *en fait* | `discourse` 179, `advmod` 40 | 224 |
| *après* | `case` 488, `advmod` 139, `mark` 124, `dep` 28 | 801 |
| *comme* | `case` 823, `mark` 288, `cc` 29 | 1 148 |
| *or* | `nmod` 52, `cc` 17, `appos` 4, `flat:foreign` 5, `advmod` 2, … | 90 |

*Puis* is a coordinator in UD French (`cc` 307 of 357), not an adverb. *Donc*, *enfin* and *en fait* are `advmod` in writing and often `discourse` in the spoken treebanks, which reflects the annotation guidelines as much as the language. The Mova dialect makes an adverb `advmod`, never `discourse` ([`dialects/mova/seeds.md#discourse-adverbs`](https://md.mova.elamur.ai/free/en/docs/dialects/mova/seeds/#discourse-adverbs); [chapter 38](https://md.mova.elamur.ai/free/en/docs/languages/fr/38-dialogue-and-discourse-markers/)). *Or* is a trap: only 19 of its 90 occurrences are the connective; most of the rest are the noun *or* "gold".

**The treebanks disagree on multiword connectives.** GSD makes *en effet* one word (*effet* `fixed`, 102 times), while Sequoia analyses it as a preposition and a noun (*effet* `obl:mod`). The spoken treebanks do the same with *par exemple*. So a count of `fixed` *en effet* finds 102 in GSD and none in Sequoia, a difference of annotation, not of usage. Counting connectives across treebanks needs expressions matched on the words.

**Frequency, written and spoken.** Per 1 000 syntactic words, punctuation included, with the relation filters of the table above (*car* only as `cc`, *si* only as `mark`, *après* only as an adverb). Written is GSD, Sequoia, PUD and ParTUT (524 236 words). Spoken is ParisStories and Rhapsodie (87 023 words):

| connective | written | per 1 000 | spoken | per 1 000 | spoken ÷ written |
| --- | --- | --- | --- | --- | --- |
| *et* (`cc`) | 10 392 | 19.82 | 1 657 | 19.04 | 1.0 |
| *mais* | 1 018 | 1.94 | 499 | 5.73 | 3.0 |
| *donc* | 246 | 0.47 | 554 | 6.37 | 13.6 |
| *parce que* | 83 | 0.16 | 274 | 3.15 | 19.9 |
| *enfin* | 73 | 0.14 | 236 | 2.71 | 19.5 |
| *en fait* | 33 | 0.06 | 191 | 2.19 | 34.9 |
| *alors* (adverb) | 295 | 0.56 | 170 | 1.95 | 3.5 |
| *quand* (`mark`) | 125 | 0.24 | 125 | 1.44 | 6.0 |
| *après* (adverb) | 42 | 0.08 | 125 | 1.44 | 17.9 |
| *quand même* | 11 | 0.02 | 89 | 1.02 | 48.7 |
| *ensuite* | 141 | 0.27 | 71 | 0.82 | 3.0 |
| *puisque* | 60 | 0.11 | 33 | 0.38 | 3.3 |
| *puis* | 296 | 0.56 | 29 | 0.33 | 0.6 |
| *car* | 169 | 0.32 | 13 | 0.15 | 0.5 |
| *lorsque* | 165 | 0.31 | 7 | 0.08 | 0.3 |
| *alors que* | 143 | 0.27 | 15 | 0.17 | 0.6 |
| *ainsi* (adverb) | 232 | 0.44 | 0 | 0 | 0 |
| *cependant* | 163 | 0.31 | 0 | 0 | 0 |
| *toutefois* | 83 | 0.16 | 0 | 0 | 0 |
| *tandis que* | 79 | 0.15 | 0 | 0 | 0 |
| *bien que* | 85 | 0.16 | 0 | 0 | 0 |
| *néanmoins* | 37 | 0.07 | 1 | 0.01 | 0.2 |
| *pourtant* | 34 | 0.06 | 7 | 0.08 | 1.2 |
| *or* (connective) | 17 | 0.03 | 2 | 0.02 | 0.7 |

The spoken sample is small (87 000 words), so its rare items rest on single digits. Three points are still clear. *Et* is equally frequent in both, but speech builds its relations from a small set: *mais*, *donc*, *parce que*, *alors*, *après*, *enfin*, *en fait*. The concessive and oppositive adverbs of writing (*cependant*, *toutefois*, *néanmoins*, *ainsi*, *bien que*, *tandis que*) are absent from the spoken corpora, which use *mais* and *quand même* for concession and *quand* for time. And *car* and *parce que* swap places (§6).

**At the start of the sentence.** The share of sentences whose first word, punctuation aside, is a connective:

| treebank | sentences | *et* | *mais* | *donc* | *alors* | *parce que* | *enfin* |
| --- | --- | --- | --- | --- | --- | --- | --- |
| GSD | 16 342 | 0.4% | 1.1% | — | 0.2% | 0.0% | 0.2% |
| Sequoia | 3 099 | 0.4% | 0.6% | — | — | — | — |
| ParisStories | 2 776 | 26.3% | 5.7% | 7.1% | 1.2% | 1.4% | 2.0% |
| Rhapsodie | 3 209 | 13.0% | 4.7% | 3.0% | 3.4% | 1.2% | 0.9% |

A quarter of the sentences of ParisStories, a corpus of spoken narratives, begin with *et*: the transcription cuts speech into short units, and *et*, *donc* and *alors* open each step of the story (§8). Written French rarely starts a sentence with a connective, and then mostly with *mais* (181 in GSD), *cependant* (71) or *ainsi* (64).

## 6. Cause: *car*, *parce que*, *puisque*, *comme*

French has four everyday causal connectives, and the grammars traditionally divide the labour among them as follows:

| connective | syntax | position | traditional account |
| --- | --- | --- | --- |
| *parce que* | subordinator, `mark` + `advcl` | after the main clause, or alone as an answer | the cause of the fact; answers *pourquoi ?*; can be clefted (*c'est parce que…*) and negated (*non pas parce que…*) |
| *car* | coordinator, `cc` + `conj` | after the main clause only | justifies the utterance; more formal; cannot be clefted or answer *pourquoi ?* |
| *puisque* | subordinator | either side | presents the cause as known to the hearer or indisputable; often justifies a speech act (Explanation*) |
| *comme* | subordinator | before the main clause | the cause as background: *Comme il pleuvait, nous sommes restés.* |

**Car and parce que.** The usual claim is that *car* gives a subjective, speaker-oriented reason and belongs to a high register, while *parce que* serves both objective and subjective causes. Blochowiak, Grisot & Degand (2020, `blochowiak-2020-what-type-subjectivity-lies-behind`, *Glossa*, CC BY 4.0) tested this on journalistic texts and a one-million-word SMS corpus, with annotation tasks. Their results do not support it. In SMS, *car* is about as frequent as *parce que* (1.09 against 1.52 per thousand words), so it is not confined to formal writing. Readers more often took *car* as presenting the information *objectively*, not subjectively. In SMS, *car* introduced events more often and *parce que* opinions more often. The authors propose two kinds of subjectivity: the type of causal relation (a cause in the world, or a reason for a belief or an act) and an evaluative, expressive subjectivity. *Parce que* carries the second more than *car*.

The treebanks show the register split more sharply. In writing *car* outnumbers *parce que* two to one (169 to 83; GSD alone 130 to 40). In the two spoken treebanks *parce que* outnumbers *car* twenty to one (274 to 13), and ParisStories has only 3 *car*. SMS, with its near-equal ratio, sits between speech and print. In GSD a *car* clause often justifies an evaluation or a piece of advice rather than giving the cause of a fact:

(1) GSD `fr-ud-train_09346` *Dommage pour eux car les plats étaient bon.* "Too bad for them, because the dishes were good" (the writer's *bon*). The *car* clause justifies *Dommage*; it causes nothing.

(2) GSD `fr-ud-test_00237` *Il vaut mieux réserver car ce petit coin de Naples est bien connu.* "Better book, because this little corner of Naples is well known": a reason for advice (a speech act).

In speech, *parce que* often stands alone. It opens a new transcription unit that explains, after the fact, what was just said:

(3) ParisStories `ParisStories_2019_devoirPhilosophie_3`–`_4` *donc je me suis dit, comment je vais faire pour rendre ce devoir ? / parce que euh, je suis pas très douée en philosophie à la base.* "so I said to myself, how am I going to hand in this assignment? / because uh, I'm not very good at philosophy to start with." This *parce que* justifies the worry, not the assignment. It behaves like *car*, which spoken French barely uses.

Sentence-initial *parce que* opens 40 sentences in ParisStories and 39 in Rhapsodie, against 5 in GSD. Such a fragment must attach to the previous sentence or turn, because its own tree has no main clause (§10, §12).

**Puisque.** *Puisque* presents its clause as already accepted, so the relation it marks is often between the clause and the speaker's right to say the other one:

(4) GSD `fr-ud-dev_00667` *Choix payant puisque le milieu de terrain inscrit le 3e but de son club dix secondes après être entré en jeu !* "A choice that paid off, since the midfielder scored his club's third goal ten seconds after coming on!" The goal is the evidence for the evaluation *payant*.

(5) Rhapsodie `Rhap_D2004-26` *alors, en fait, vous êtes, euh, liée à la France, puisque vous êtes française.* "so, actually, you are, uh, linked to France, since you are French." The speaker states the obvious and uses *puisque* to mark it as obvious.

LEXCONN counts *puisque* among the connectives of Explanation* (§4). Unlike *car*, it is not rare in speech (60 written, 33 spoken).

**Result: donc, alors, ainsi, par conséquent.** *Donc* is the commonest result connective, but in speech it also resumes a narrative (*donc euh j'ai fait la conduite accompagnée au lycée*, ParisStories `ParisStories_2019_peripitiesVoiture_2`) or brings back a question. In writing it is often a mid-clause adverb of inference: *C'est un affluent de l'Aube en rive gauche, donc un sous-affluent de la Seine.* (GSD `fr-ud-train_07771`). *Par conséquent* (10 in GSD, none in speech) belongs to writing. *Ainsi* is either result ("thus") or manner ("in this way"), and the FDTB had to separate the two (§3).

## 7. Contrast and concession

**Mais** is the second most frequent connective and covers both contrast (*X, but Y differs*) and concession (*X, but Y despite X*). The argumentative tradition of French linguistics (Anscombre & Ducrot; not open, *Wanted*) analyses *p mais q* this way: *p* argues for a conclusion *r*, *q* argues for not-*r*, and *q* is stronger. The analysis explains why *mais* can link sentences that share no topic, as in *Il fait beau, mais j'ai du travail* "It's fine, but I have work", where the conclusion is "let's go out" or not. *Mais* is `cc` in 1 518 of its 1 564 occurrences. When it opens a sentence, it is still `cc` of the root of that sentence, so in UD it attaches inside the sentence and does not link the two sentences. The link to the previous sentence is not in the tree.

**Or** introduces a new premise that turns the argument. It is the "minor premise" connective of the syllogism, typical of argument and legal prose:

(6) GSD `fr-ud-dev_01069` *Or, la mère de Leslie était invalide depuis sa naissance.* "Now, Leslie's mother had been an invalid since birth." *Or* is `cc` of the root *invalide*, again inside its own sentence.

*Or* has no single English equivalent (*now*, *yet*, *however* each capture part of it), and it is rare: 17 written, 2 spoken.

**The concessive and oppositive adverbs** *cependant*, *pourtant*, *toutefois*, *néanmoins* and *en revanche* / *par contre* are written French: together about 0.7 per 1 000 written words, and almost none in the spoken corpora (§5). LEXCONN separates **Opposition** (*cependant*, *malgré tout*: the second segment goes against an expectation) from **Concession** (*même si*, *bien que*: the first segment is granted and does not prevent the second). *En revanche* and *par contre* mark plain contrast between two parallel facts: *Si ses publications ont été peu nombreuses, la portée de son enseignement, en revanche, a été considérable.* (GSD `fr-ud-train_03288`). *Par contre* was long criticised by purists, but it is in common use: GSD has 21 *par contre* against 27 *en revanche*, the former in reviews such as *Par contre l'accueil est impeccable…* (GSD `fr-ud-test_00273`).

**Subordinating contrast and concession.** *Alors que* and *tandis que* are temporal in origin ("while") and now mostly contrastive. In GSD, *alors que* 123 and *tandis que* 63 are `mark`. Many of these clauses contrast two parallel facts, as in *84,0% des logements sont possédés alors que 16,0% sont loués.* (GSD `fr-ud-train_08136`). Others keep the temporal frame, as in *Mais un jour, alors qu'il survole l'Amazonie, leur avion s'écrase dans la forêt.* (GSD `fr-ud-train_01965`). Relex's authors give *tandis que* as their example of a connective whose relation depends on context, Contrast or Background (§3). The concessive *bien que* takes the subjunctive and *même si* the indicative ([chapter 13](https://md.mova.elamur.ai/free/en/docs/languages/fr/13-verbs/), [chapter 24](https://md.mova.elamur.ai/free/en/docs/languages/fr/24-coordination-subordination/)). *Bien que* occurs 85 times in writing and never in the spoken treebanks, where *même si* and *mais* take its place.

**Quand même** "all the same, still" is the concessive adverb of speech: 89 occurrences in speech against 11 in writing, the strongest spoken skew in the table of §5. It also works as an intensifier (*c'est quand même bizarre* "it's really weird though"), so not every *quand même* marks a relation ([chapter 38](https://md.mova.elamur.ai/free/en/docs/languages/fr/38-dialogue-and-discourse-markers/)).

## 8. Time and narrative

### 8.1 Temporal connectives

*Puis* and *ensuite* mark the next event; *alors* marks the next event or the consequence; *après* is a preposition, a subordinator (*après que*) or, in speech, an adverb "afterwards; then again". Bras, Le Draoulec & Vieu (2001, `bras-2001-temporal-information-discourse-relations-narratives`, NC: read only) compared *puis* with *un peu plus tard* "a bit later" in SDRT. They argue that *puis* marks Narration proper and blocks a Result reading. *Un peu plus tard* blocks Narration and allows only a weaker, purely temporal succession, and it is compatible with Result. Two connectives with nearly the same temporal content thus differ in the discourse relations they allow.

In written narration *puis* chains events and also items in a description:

(7) GSD `fr-ud-train_14479` *Les Drangiens furent soumis par les Mèdes, puis par Cyrus le Grand.* "The Drangians were subjugated by the Medes, then by Cyrus the Great." Here *puis* is `cc` on the second agent, *Cyrus*, a `conj` of *Mèdes*: the succession is between two events that share one verb.

(8) GSD `fr-ud-train_00686` *Arbuste, parfois densément ramifié, avec des rameaux d'abord laineux puis glabres.* "A shrub, sometimes densely branched, with branches woolly at first, then hairless." This is the succession of two states in a botanical description, not a narrative sequence.

**Après in speech.** Herreño Castañeda & Sillaire (2025, `castaneda-2025-annotation-de-marqueurs-discursifs-le`) studied *après* in the CODIM corpus, about 110 million tokens of spoken, written and online French. A rule-based pass marked 848 occurrences as discourse marker and 75 151 as not, and left 70 059 undecided, more than half of them in the oral and online data. Linking discourse units, *après* can be additive (listing), consecutive, contrastive ("that said, mind you") or meta-discursive. To find the contrastive use, their protocol first excludes fixed phrases (*après-guerre*) and *après* next to a duration, an event noun or a place. It then looks for neighbouring markers (*bon après*, *mais après*) and finally asks whether the two situations are opposed. With it, agreement rose from κ 0.54 to 0.69. In the press, contrastive *après* hardly occurred. The treebanks agree: ParisStories has 82 adverbial *après* against 9 prepositional ones, GSD 40 against 317.

### 8.2 Tense and discourse

French narrative tenses carry discourse relations of their own. In the classic analysis of written narrative (Kamp & Rohrer 1983 on French tenses in DRT; Weinrich, *Le Temps*; both not open, *Wanted*), the *passé simple* moves the story forward: each new event follows the last (Narration). The *imparfait* sets a background state or an ongoing frame around the current event (Background). The *plus-que-parfait* moves back (Flashback). In speech and in most modern writing the *passé composé* takes over the role of the *passé simple*, and the narrative present is common.

Finite indicative verbs of the narrative tenses (lexical verbs and copulas, not auxiliaries). The *passé composé* is counted as an auxiliary in the present with a participle:

| treebank | *passé simple* | *imparfait* | *passé composé* |
| --- | --- | --- | --- |
| GSD | 1 222 | 1 547 | 2 908 |
| Sequoia | 98 | 296 | 689 |
| PUD | 97 | 203 | 454 |
| ParisStories | 0 | 1 277 | 767 |
| Rhapsodie | 2 | 402 | 404 |

ParisStories is a corpus of personal narratives, and it has no *passé simple* at all. Its stories run on the *passé composé* for events, the *imparfait* for background (more imparfaits than passé composés), and connectives for the steps: *et* (26% of sentence starts), *donc* (7%), *alors*, *après*, *et puis*. The written *passé simple* of GSD sits in encyclopaedic history (*Les Drangiens furent soumis…*, ex. 7). So a reader that infers Narration from the *passé simple* has a cue in written history and fiction ([chapter 13](https://md.mova.elamur.ai/free/en/docs/languages/fr/13-verbs/)) but none in speech, where the cue is the connective and the *passé composé*.

Narrative order by connectives alone also misleads. *Alors* after an *imparfait* frame marks the event that breaks in (*il lisait; alors on a sonné*). After an event it marks the consequence. *Alors que* with an *imparfait* or present keeps a simultaneous background (ex. above, *alors qu'il survole l'Amazonie*). These are the interactions of tense, aspect and connective that Grisot (2018; see the English chapter §8) measures for English and French.

## 9. Implicit relations

Most relations in a narrative, and many in argument, have no connective. The FDTB authors estimated, from the share of explicit relations found in other languages (about half), that the ANNODIS texts contain some 1 600 connectives (Danlos et al. 2015). DiscoGeM 2.0 gives the cross-language picture. When crowd workers inserted connectives into implicit relations of parallel texts, the French readings did not always match the English or German ones. The translation sometimes made explicit, or changed, the relation the original left implicit (Yung et al. 2024). Translation into or out of French therefore cannot carry implicit relations across unchanged.

| cue | relation it suggests | French example |
| --- | --- | --- |
| two events in the order told, *passé simple* or *passé composé* | Narration | *Il ouvrit la porte. Il entra.* |
| an event, then an *imparfait* state | Background | *Il sortit. Il pleuvait.* |
| an event, then a plausible cause | Explanation | *Max est tombé. Jean l'a poussé.* |
| a general statement, then a specific one | Elaboration, Instance | *Les renards sont rusés. Celui-ci a trompé un corbeau.* |
| a colon | Elaboration, Explanation | *Un seul problème : la porte était fermée.* |
| a question, then an assertion | Question–Answer | *Pourquoi s'est-elle assise ? La côte était raide.* |
| a gerund (*en* + participle) | Manner, Means, Cause, Simultaneity | *En travaillant, il a réussi.* |
| a detached participle or adjective | Cause, Background | *Fatigué, il s'est couché.* |

The last two rows are French-specific constructions whose relation is underspecified. *En travaillant* can be the means, the cause, or a simultaneous action ([chapter 13](https://md.mova.elamur.ai/free/en/docs/languages/fr/13-verbs/)). A detached participle (*La production étant déficitaire, on importa alors des olives d'Algérie*, GSD `fr-ud-train_05152`) is usually a cause or a background.

**Juxtaposition in the trees.** UD marks two juxtaposed clauses in one sentence as `parataxis`:

| treebank | words | `parataxis` (all subtypes) | per 1 000 | of which `:insert` / `:parenth` |
| --- | --- | --- | --- | --- |
| GSD | 400 385 | 1 116 | 2.79 | 183 `:insert` |
| Sequoia | 70 545 | 290 | 4.11 | 126 `:insert` |
| PUD | 24 726 | 107 | 4.33 | — |
| ParTUT | 28 580 | 7 | 0.24 | — |
| ParisStories | 42 789 | 45 | 1.05 | 27 `:parenth` |
| Rhapsodie | 44 234 | 59 | 1.33 | 15 `:insert`, 39 `:parenth` |

The spoken treebanks have *fewer* paratactic links than the written ones, though speech is more paratactic. Their transcriptions cut juxtaposed clauses into separate sentences, so the juxtaposition falls between trees, where UD records nothing. Most of what remains in speech is parenthetical (`:parenth`). ParTUT's near-zero is a convention of its conversion. Read across treebanks, `parataxis` measures annotation practice as much as the language.

## 10. Questions under discussion

The QUD view (Roberts 1996/2012; English chapter [§9](https://md.mova.elamur.ai/free/en/docs/languages/en/36-discourse-relations/#9-questions-under-discussion)) treats a discourse as answers to a stack of open questions. Speakers often pose the question themselves: the *Pourquoi ? Parce que…* of argument, or the opening of an oral recipe, *donc comment je fais les gougères ?* (ParisStories `ParisStories_2019_cuisineApproximative_1`), which the rest of the story answers. Cleft and pseudo-cleft sentences (*Ce qui m'étonne, c'est que…*, *C'est là que…*) state the question in the sentence itself. Their information structure is in [chapter 29](https://md.mova.elamur.ai/free/en/docs/languages/fr/29-ellipsis-word-order-information-structure/), and their presupposition in [chapter 33](https://md.mova.elamur.ai/free/en/docs/languages/fr/33-implicature-and-presupposition/).

The French answer fragment *Parce que…* is the common case of an answer without a main clause (§6). A QUD reader must accept a *parce que* fragment as an answer to *pourquoi*, and a *pour* + infinitive fragment as an answer to *pour quoi faire ?* The English QUD module does not yet do even the English equivalent (§12). The FQB treebank, 2 289 questions with 172 *quand* and 19 *pourquoi* among their wh-words, is a source of French questions but has no answers.

## 11. Segmentation and parsing for French

| task | French data | state, by the open papers |
| --- | --- | --- |
| EDU segmentation, written | ANNODIS (DISRPT) | near its plateau across DISRPT corpora (Braud et al. 2024, English chapter §7); no French-only figure read here |
| EDU segmentation, conversation | CID; a new meeting corpus | F ≈ 0.86 on meetings; below written scores |
| connective identification | FDTB1; Relex automata | automata F1 0.76 against FDTB; no DISRPT task for French |
| connective → relation | LEXCONN; ConcoLeDisCo; Relex | Relex F1 0.59 on unseen connectives (19 relations) |
| relation classification, RST | RST-DT in translation | DMRST F1 0.54 (English 0.65) |
| implicit relations | DiscoGeM 2.0 | distributions of readings; no French parser result here |
| full SDRT parsing | ANNODIS | not reported in the papers read here |

**Segmenting conversation.** Hunter, Prévot & Muller (2023, `prevot-2023-comparing-methods-segmenting-elementary-discourse`) segmented the Corpus of Interactional Data (CID), conversational French, in two ways: by fine-tuning an existing segmenter on the manual EDUs, and by data programming, where hand-written labelling rules train a weakly supervised model. The two reached similar F-scores, and the rules needed far less annotation. Conversation is made of short contributions and one-word non-sentential units (answers, feedback), which segmenters trained on written text handle badly. Prévot, Bertrand & Hunter (2025, `prevot-2025-segmenting-large-french-meeting-corpus`) added 20 hours of manually segmented French meetings among three or four people, and 80 hours segmented automatically. A model fine-tuned on it scored F ≈ 0.86, still below written texts.

**Weak supervision for relations.** Maachou, Braud & Muller (2025, `maachou-2025-supervision-faible-pour-la-classification`) combine heuristics and pretrained models as weak labellers for relation classification across mismatched label sets, and come close to full supervision with a small part of the data. Badene et al. (2019, `badene-2019-apprentissage-faiblement-supervise-de-la`) use data programming for SDRT attachment. Both work on English corpora (RST-DT and PDTB; the chat corpus STAC). Their methods suit French, where gold data is scarce, but neither reports a French result.

**What the papers say for Mova.** Relex and ConcoLeDisCo show that the relation of a connective can be learned from cheap signals: monosemous connectives, or alignment with English. Pastor et al. show that *si* is a reliable cue and *et* is not. The *après* study shows that a marker's discourse use can be ambiguous even for expert annotators (κ 0.69 at best), and that genre decides much of the answer. A French reader should start from the connectives whose relation is stable: *si*, *parce que*, *bien que*, *pour que*, *puis*. It should treat *et*, *donc*, *alors*, *après* and *enfin* as uncertain.

## 12. How Mova handles it

Checked against the code on 2026-11-06.

### 12.1 What exists, for English

Mova keeps discourse relations as links between frames, not as a separate tree. The frame reader ([`prag/src/frames.rs`](https://md.mova.elamur.ai/free/en/docs/prag/), `set_cause` and `set_next`) sets them from the UD relation of a clause and its marker word. The English chapter [36 §11](https://md.mova.elamur.ai/free/en/docs/languages/en/36-discourse-relations/#11-how-mova-reads-discourse-relations) shows a run.

| rule in `frames.rs` | depends on |
| --- | --- |
| `advcl` marked by *because, since, cos, cause, cuz* (or *as* on `advcl`) → `cause` of the main frame | English lemmas |
| *so, therefore, thus* (not *so that*) → the clause just before is the `cause`, and `next` | English lemmas |
| *so/such … that* → `cause` of the result | English lemmas |
| *if, unless* → the `cond` flag | English lemmas |
| purpose *to* + infinitive, *by* + V-ing → `cause` | English lemmas and UD relations |
| *after, once, when, whenever* / *before, until, till* → `next` in the right direction | English lemmas |
| `ccomp` of a verb of saying or thinking, quoted speech → `quote` | English verb lists |
| `conj` or `parataxis`, or *then* → `next` (the told order) | **UD relations only** |

The QUD stack ([`world/src/qud.rs`](https://md.mova.elamur.ai/free/en/docs/world/)) recognises answers to *why* through the list `REASON` = *because, since, so*, and the wh-types through English question words. The Manner inference "and = in that order" ([`prag/src/infer.rs`](https://md.mova.elamur.ai/free/en/docs/prag/), `maxims`) uses English lists of stative verbs (`STATIVE`) and reordering words (`REORDER`).

### 12.2 What happens to French

**Nothing in this layer reads French.** No pipeline passes a French tree to the frame reader. The reader does not check the language: `prag roles <in.conllu>` accepts any CoNLL-U file. But every rule except the last tests an English lemma, so on a French tree only the structural rule would fire. Read from the code (not run on French), the outcome would be this. *Il purifie tout car il supprime les odeurs* (*car* `cc` on a `conj`) would get `next`, a sequence where French means a cause. *Le crédit était mort parce que…* (*parce* `mark`) would get no link. *Puis* (`cc` + `conj`) would get the right `next`, by accident. A French reader needs:

1. **A French connective table** keyed on the word sequence and the UD relation, not on `fixed` (§5). LEXCONN is NC-ND and cannot be carried into a release, so the table must be written in Mova's own words from the open papers and checked against the trees; the counts of §5 give its first entries.
2. **Cause on `cc` + `conj`** for *car* (and *donc* as `cc`), which the English rules never needed.
3. **Metatalk links** for *puisque*, *car* and *donc* on a speech act (Explanation*, Result*, §4). A plain `cause` link would say that a goal caused an evaluation (ex. 4).
4. **Cross-sentence attachment** of sentence-initial *parce que*, *mais*, *donc*, *or*, which UD attaches inside their own sentence. In the spoken treebanks a quarter (Rhapsodie) to nearly half (ParisStories) of the sentences start with a connective.
5. **Tense from FEATS.** The *passé simple* / *imparfait* contrast (§8.2) is in the treebank's `Tense` feature. Mova's parser sees only forms and PTB tags, which have neither tense ([chapter 30](https://md.mova.elamur.ai/free/en/docs/languages/fr/30-pragmatics-overview/) §9.2).

### 12.3 The French pragmatics layer for the Eel, and the meta-pragmatics

The Eel, the learner that improves Mova's trees and pragmatics, schedules its rounds by kind. In the code in development on 2026-11-06, one kind is **`prag-fr`**, a gated round for French pragmatics ([`tools/eel/src/schedule.rs`](https://md.mova.elamur.ai/free/en/docs/tools/eel/), `KINDS`; [`tools/eel/src/native.rs`](https://md.mova.elamur.ai/free/en/docs/tools/eel/)). Such a round runs a pinned native executable on the CPU. The Eel itself checks the pinned dev sample, the disjointness of train and dev keys and the reported metric. It installs a candidate only on a dev gain, and it queues proposals for review only. **The French pragmatics executable is not written yet.** There is no French connective table and no measurement. The schedule gives the work a slot and a gate, nothing more.

The **meta-pragmatics** is the planned language-independent layer: one schema of relations and acts that every language's reader writes to, with each language's connectives mapped into it. It is a direction, not code. What the readers share today is the UD relations they start from and the English frame fields (`cause`, `next`, `quote`, `cond`). §3 shows why the schema cannot simply borrow one framework's labels. LEXCONN's SDRT relations and the PDTB senses coincide only on Concession and Condition (Laali & Kosseim 2017), and implicit relations shift across translation (DiscoGeM 2.0). The mappings must stay explicit and revisable.

### 12.4 Not yet

- No French connective list, no French link rule, no French QUD reasons (*parce que*, *car*, *puisque*, *comme*).
- No metatalk relations (Explanation*, Result*) in any language; no Contrast, Concession, Opposition or Elaboration fields.
- No cross-sentence attachment of sentence-initial connectives.
- No discourse tree or graph and no EDU segmentation, for English or French.
- None of the French discourse resources of §3 is held in `$MOVA_DATA`. The open ones (ConcoLeDisCo, Relex) are not used even for measurement.
- The `prag-fr` round has a schedule slot and a gate, but no executable.

## In Mova

- Links: [`prag/src/frames.rs`](https://md.mova.elamur.ai/free/en/docs/prag/) (`set_cause`, `set_next`, `quote`); inference: [`prag/src/infer.rs`](https://md.mova.elamur.ai/free/en/docs/prag/) (`maxims`, `STATIVE`, `REORDER`); QUD: [`world/src/qud.rs`](https://md.mova.elamur.ai/free/en/docs/world/) (`REASON`).
- Reading a CoNLL-U file: `prag roles` ([`prag/src/main.rs`](https://md.mova.elamur.ai/free/en/docs/prag/)).
- The Eel's rounds: [`tools/eel/src/schedule.rs`](https://md.mova.elamur.ai/free/en/docs/tools/eel/), [`tools/eel/src/native.rs`](https://md.mova.elamur.ai/free/en/docs/tools/eel/) (in development, 2026-11-06).
- The Mova dialect on `discourse`: [`dialects/mova/seeds.md#discourse-adverbs`](https://md.mova.elamur.ai/free/en/docs/dialects/mova/seeds/#discourse-adverbs).
- English counterpart: [36. Discourse relations and coherence](https://md.mova.elamur.ai/free/en/docs/languages/en/36-discourse-relations/).

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- Richard, A. et al. 2024. FRACAS: a FRench Annotated Corpus of Attribution relations in newS. LREC-COLING. `richard-2024-fracas-french-annotated-corpus-attribution` (CC BY-NC 4.0: informs only).
- Bras, M., Le Draoulec, A., Vieu, L. 2001. Temporal Information and Discourse Relations in Narratives: the role of French connectives *puis* and *un peu plus tard*. ACL workshop. `bras-2001-temporal-information-discourse-relations-narratives` (CC BY-NC-SA 3.0: informs only).
- Herreño Castañeda, P., Sillaire, M. 2025. Annotation de marqueurs discursifs : le cas de la désambiguïsation de *après*. RECITAL. `castaneda-2025-annotation-de-marqueurs-discursifs-le` (CC BY 4.0).
- Hunter, J., Prévot, L., Muller, P. 2023. Comparing Methods for Segmenting Elementary Discourse Units in a French Conversational Corpus. NoDaLiDa. `prevot-2023-comparing-methods-segmenting-elementary-discourse` (CC BY 4.0).
- Prévot, L., Bertrand, R., Hunter, J. 2025. Segmenting a Large French Meeting Corpus into Elementary Discourse Units. SIGdial. `prevot-2025-segmenting-large-french-meeting-corpus` (CC BY 4.0).
- Maachou, K., Braud, C., Muller, P. 2025. Supervision faible pour la classification des relations discursives. TALN. `maachou-2025-supervision-faible-pour-la-classification` (CC BY 4.0).
- Badene, S. et al. 2019. Apprentissage faiblement supervisé de la structure discursive. TALN. `badene-2019-apprentissage-faiblement-supervise-de-la` (CC BY 4.0).
- Wanted (not open): Halliday & Hasan 1976; Asher & Lascarides 2003; Anscombre & Ducrot, *L'argumentation dans la langue* (1983); Kamp & Rohrer 1983; Weinrich, *Le Temps* (1973).
- Universal Dependencies French treebanks, UD 2.18: GSD, ParisStories, Rhapsodie (CC BY-SA 4.0; short quotations with `sent_id`), Sequoia, FQB (LGPL-LR), PUD (CC BY-SA 3.0), ParTUT (CC BY-NC-SA 4.0: counts only). Counts made on 2026-11-06 from UD_French-*, all splits together, one count per syntactic word, punctuation in the denominator; multiword connectives matched on the head word plus its `fixed` dependents (*qu'* normalised to *que*).
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