--- title: ge is the most common measure word, used for people and many things,… — Olympiad: measure words and characters as pictur… · tree and pragmatics description: ge is the most common measure word, used for people and many things, as in yí ge rén and liǎng ge píngguǒ (two apples); in fast talk people use ge a lot. Who acts: ge, people. A sentence of the lesson «Olympiad: measure words and characters as pictures ★★★» of the chinese street course of Mova's pri --- [Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/corpora/school/chinese-street/32-olympiad-measure-words-and-picture-characters/6/) [home](https://md.mova.elamur.ai/free/en/) / [corpora](https://md.mova.elamur.ai/free/en/corpora/) / [school](https://md.mova.elamur.ai/free/en/corpora/school/) / [Chinese street](https://md.mova.elamur.ai/free/en/corpora/school/chinese-street/) / [Olympiad: measure words and characters…](https://md.mova.elamur.ai/free/en/corpora/school/chinese-street/32-olympiad-measure-words-and-picture-characters/) / 6 # Olympiad: measure words and characters as pictures ★★★, sentence 6 ge is the most common measure word, used for people and many things, as in yí ge rén and liǎng ge píngguǒ (two apples); in fast talk people use ge a lot. **Who acts:** ge, people · **What happens:** be, use · **To what, where:** common measure word, ge, fast talk This is a sentence of the lesson «Olympiad: measure words and characters as pictures ★★★» of the chinese street course of Mova's primary school. The page gives its syntax tree — a dependency tree in the style of Universal Dependencies — and its pragmatics clause by clause: who acts (ge, people), what happens, when and where, as Mova's frames read it from the tree. ## The tree {#tree} ```conllu # sent_id = school:chinese-street:032-olympiad-measure-words-and-picture-characters.lesson:6 # text = ge is the most common measure word, used for people and many things, as in yí ge rén and liǎng ge píngguǒ (two apples); in fast talk people use ge a lot. # source = school lesson (ours) # course = chinese-street # lesson = 032-olympiad-measure-words-and-picture-characters.lesson # annotation = Mova annot: Rust (en) → Haiku 5.5 (medium, Batches API) patches; gates UD 2.18; agreed by treeagree rules (Stanza, Trankit, spaCy trf): R7-rel-agree ×1 1 ge ge NOUN NN Number=Sing 7 nsubj _ _ 2 is be AUX VBZ Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin 7 cop _ _ 3 the the DET DT Definite=Def|PronType=Art 7 det _ _ 4 most most ADV RBS Degree=Sup 5 advmod _ _ 5 common common ADJ JJ Degree=Pos 7 amod _ _ 6 measure measure NOUN NN Number=Sing 7 compound _ _ 7 word word NOUN NN Number=Sing 0 root _ _ 8 , , PUNCT , _ 9 punct _ _ 9 used use VERB VBN Tense=Past|VerbForm=Part|Voice=Pass 7 acl _ _ 10 for for ADP IN _ 11 case _ _ 11 people people NOUN NNS Number=Plur 9 obl _ _ 12 and and CCONJ CC _ 14 cc _ _ 13 many many ADJ JJ Degree=Pos 14 amod _ _ 14 things thing NOUN NNS Number=Plur 11 conj _ _ 15 , , PUNCT , _ 20 punct _ _ 16 as as ADP IN ExtPos=ADP 20 case _ _ 17 in in ADP IN _ 16 fixed _ _ 18 yí yí ADP IN _ 20 case _ _ 19 ge ge NOUN NN Number=Sing 20 compound _ _ 20 rén rén NOUN NN Number=Sing 9 parataxis _ _ 21 and and CCONJ CC _ 24 cc _ _ 22 liǎng liǎng ADJ JJ Degree=Pos 24 amod _ _ 23 ge ge NOUN NN Number=Sing 24 compound _ _ 24 píngguǒ píngguǒ NOUN NN Number=Sing 20 conj _ _ 25 ( ( PUNCT -LRB- _ 27 punct _ _ 26 two two NUM CD NumForm=Word|NumType=Card 27 nummod _ _ 27 apples apple NOUN NNS Number=Plur 24 appos _ _ 28 ) ) PUNCT -RRB- _ 27 punct _ _ 29 ; ; PUNCT , _ 34 punct _ _ 30 in in ADP IN _ 32 case _ _ 31 fast fast ADJ JJ Degree=Pos 32 amod _ _ 32 talk talk NOUN NN Number=Sing 34 obl _ _ 33 people people NOUN NNS Number=Plur 34 nsubj _ _ 34 use use VERB VBP Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin 7 parataxis _ Agree=R7-rel-agree|Haiku=7:conj 35 ge ge NOUN NN Number=Sing 34 obj _ _ 36 a a DET DT Definite=Ind|PronType=Art 37 det _ _ 37 lot lot NOUN NN Number=Sing 34 obl:unmarked _ _ 38 . . PUNCT . _ 7 punct _ _ ``` ## Pragmatics {#pragmatics} - form: statement - act: assert - voice: narrator - polarity: none - teacher: kept the draft | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **is a** | present | ge | the common measure word | | | | | tree rules | | 2 | **use** | participle | | the common measure word *not said here* | | | | for people and many things | vn eat-39.1 «NP V»: agent=Agent | | 3 | **use** | present | people | ge | | fast talk | | a lot *obl:unmarked* | vn eat-39.1 «NP V NP»: agent=Agent ge=Patient | One row per clause the reader finds. «not said here»: a role filled from the clause above. «roles by»: a VerbNet class and frame when one fits the verb, else the reader's rules on the tree. **Licence: [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)**, as the whole of Mova corpus 0.4, of which this treebank (the agreed school, `mova-school-agreed-en.conllu`) is part. The lessons were written for Mova's primary school. Sentence `school:chinese-street:032-olympiad-measure-words-and-picture-characters.lesson:6`. **The tree:** Mova annot: Rust (en) → Haiku 5.5 (medium, Batches API) patches; gates UD 2.18; agreed by treeagree rules (Stanza, Trankit, spaCy trf): R7-rel-agree ×1. **The frames** are read from the tree by Mova's frames reader (`prag`) when this page is built, the lesson read in order, so a pronoun may be resolved from an earlier sentence. See the [release 0.4](https://md.mova.elamur.ai/free/en/releases/0.4/). - ← previous: [Olympiad: measure words and characters…, 5](https://md.mova.elamur.ai/free/en/corpora/school/chinese-street/32-olympiad-measure-words-and-picture-characters/5/) - next →: [Olympiad: measure words and characters…, 7](https://md.mova.elamur.ai/free/en/corpora/school/chinese-street/32-olympiad-measure-words-and-picture-characters/7/) - ↑ back to [the lesson](https://md.mova.elamur.ai/free/en/corpora/school/chinese-street/32-olympiad-measure-words-and-picture-characters/)