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# (Pre-)Annotation of Topic-Focus Articulation in Prague Czech-English Dependency Treebank

**Authors:** Jiří Mírovský, Kateřina Rysová, Magdaléna Rysová, Eva Hajičová · **Year:** 2013 · **Venue:** Proceedings of the Sixth International Joint Conference on Natural Language Processing (IJCNLP 2013) **Link:** [aclanthology.org/I13-1007](https://aclanthology.org/I13-1007/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) (ACL Anthology, before 2016) — summary only

[**2** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/mirovsky-2013-pre-annotation-topic-focus-articulation/) of the 140673 papers whose bibliographies we read[Proceedings of the Sixth International Joint Conference on Natural Language Processing](https://aclanthology.org/volumes/I13-1/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/I13-1007/)
- [PDF](https://aclanthology.org/I13-1007.pdf)

**Authors (4)**

1. Jiří Mírovský
2. Kateřina Rysová
3. Magdaléna Rysová
4. Eva Hajičová

Citations and author metrics from OpenAlex (); authors with the same name are not always told apart.

## What it is about

The paper reports the first step of annotating topic-focus articulation (TFA) in the Czech part of the Prague Czech-English Dependency Treebank. The annotation follows the guidelines of the Prague Dependency Treebank, based on Functional Generative Description. Each node is marked as contextually bound non-contrastive (t), contextually bound contrastive (c) or contextually non-bound (f). An automatic pre-annotation has 12 steps, using rules such as coreference, the "anaphor" relation and the verb's position. It marks over 40% of the nodes. Its distinction between bound and non-bound nodes is about 96% correct on manually checked texts. The annotator changed the pre-annotated value in 294 cases, 3.7% of the pre-annotated nodes. Only 0.8% of the "t" nodes and 5.4% of the "f" nodes were changed, and the "c" value was never set automatically.

## Ideas

- I1. Write the TFA pre-annotation as a list of rules in `prag`, one rule per step, each with a count of nodes it marks and a count of later changes, as in the paper's Table 1 and Table 2. This makes each rule's error rate visible.
- I2. Use the coreference links from `coref` as the "given" test for a node: a node whose referent has an earlier mention is a candidate for the bound value "t". Measure the step's precision on a checked sample.
- I3. Use the information-structure labels in word order. In `en/src/lin.rs`, a focus-final rule could be tested against the linearisation the corpus shows.
- I4. Keep the "c" value out of automatic output, as the paper does, and report it as a gap, not a zero.

## For Mova

The chapter is [29. Ellipsis, word order and information structure](https://md.mova.elamur.ai/free/en/docs/languages/en/29-ellipsis-word-order-information-structure/). The code is `prag/src/roles.rs` and `en/src/lin.rs`, with `coref` for the given test. The measure is the rule-by-rule agreement with a hand-checked sample, plus the number of changed values per rule, as in Table 2. The Czech corpus is not used. The ideas are for English only.

Topics: [Coreference resolution](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/) · [Treebanks](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work.

```
@inproceedings{mirovsku2013pre,
  title = {{(Pre-)Annotation of Topic-Focus Articulation in Prague Czech-English Dependency Treebank}},
  author = {Mírovský, Jiří and Rysová, Kateřina and Rysová, Magdaléna and Hajičová, Eva},
  booktitle = {Proceedings of the Sixth International Joint Conference on Natural Language Processing},
  year = {2013},
  url = {https://aclanthology.org/I13-1007/}
}
```

- [← previous The Penn Discourse Treebank](https://md.mova.elamur.ai/free/en/docs/papers/miltsakaki-2004-penn-discourse-treebank/)
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## References

19 references, 2 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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