SciCorp: A Corpus of English Scientific Articles Annotated for Information Status Analysis

What it is about

SciCorp is 14 full scientific papers (genetics and computational linguistics, 61K tokens) in which every definite noun phrase (8,708) is labelled with an information status and, where applicable, linked: given (with a coreference link, including synonyms and short forms), associative (bridging, with a link to its anchor), description (a definite that carries its own identification: the fact that…, the X of Y, superlatives, a restrictive relative), unused (known from general knowledge), deictic, predicative, idiom; plus attributes generic and part of compound. Bare plurals and abstract (clausal) antecedents are excluded. Three annotators reached Fleiss kappa 0.68–0.73 overall; given, deictic and idiom were easy, associative, description, unused and predicative hard; links 0.81 (coreference) and 0.62 (bridging); generic only 0.51. Scientific text uses many abstract entities and definite descriptions that need domain knowledge.

Ideas

• I1. A «self-identifying definite» filter for coref: a definite whose own modifiers identify it (superlative, ordinal, the fact/idea that + clause, a restrictive relative clause, the N of + proper name) is usually a first mention, not an anaphor. Such a mention should not be linked by the head-based sieves to an earlier same-head mention whose identifying modifier differs. Add to coref/src/sieve.rs with the reason in coref explain; measure precision of strict_a/relaxed on GUM dev.
• I2. The low agreement on generic (0.51) matches Mova's error of linking repeated generic groups («some politicians» ~ «some politicians»): do not expect a reliable generic label; instead keep the existing rule that quantified and indefinite mentions are not linked except on exact match, and check how many exact errors on GUM dev are bare or quantified plurals before adding anything.

For Mova

35. Reference and coreference §2 (givenness), §3.2 (bridging), §4 (non-referential and generic uses). Code: coref/src/sieve.rs, coref/src/mention.rs. Measures: sieve precision and CoNLL F1 on GUM dev.

Topics: Coreference resolution

Cite

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

@inproceedings{roesiger2016scicorp,
  title = {{SciCorp: A Corpus of English Scientific Articles Annotated for Information Status Analysis}},
  author = {Roesiger, Ina},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
  year = {2016},
  url = {https://aclanthology.org/L16-1275/}
}

References

18 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Batista-Navarro, R. T. and Ananiadou, S. (2011). Building a coreference-annotated corpus from the domain of biochemistry. In Proceedings of BioNLP 2011 Workshop, pages 83–91. Association for Computational Linguistics. find
2. Baumann, S. and Riester, A. (2012). Referential and Lexical Givenness: semantic, prosodic and cognitive aspects. In Gorka Elordieta et al., editors, Prosody and Meaning, number 25 in Interface Explorations. Mouton de Gruyter, Berlin. find
3. Clark, H. H. (1975). Bridging. In Proceedings of the 1975 workshop on Theoretical issues in natural language processing, pages 169–174. Association for Computational Linguistics. find
4. Cohen, K. B., Lanfranchi, A., Corvey, W., Baumgartner Jr, W. A., Roeder, C., Ogren, P. V., Palmer, M., and Hunter, L. (2010). Annotation of all coreference in biomedical text: Guideline selection and adaptation. In Proceedings of BioTxtM 2010: 2nd workshop on building and evaluating resources for biomedical text mining, pages 37–41. find
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7. Kaplan, D., Iida, R., Nishina, K., and Tokunaga, T. (2012). Slate – a tool for creating and maintaining annotated corpora. Journal for Language Technology and Computational Linguistics, pages 89–101. find
8. Landis, J. R. and Koch, G. G. (1977). The measurement of observer agreement for categorical data. biometrics, pages 159–174. find
9. Markert, K., Hou, Y., and Strube, M. (2012). Collective classification for fine-grained information status. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers-Volume 1, pages 795–804. Association for Computational Linguistics. find
10. Ng, V. (2010). Supervised noun phrase coreference research: The first fifteen years. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pages 1396–1411. Association for Computational Linguistics. find our card
11. Nissim, M., Dingare, S., Carletta, J., and Steedman, M. (2004). An annotation scheme for information status in dialogue. LREC 2004. find
12. Poesio, M. and Vieira, R. (1998). A corpus-based investigation of definite description use. Computational linguistics, 24(2):183–216. find
13. Prince, E. F. (1981). Toward a taxonomy of given-new information. In Radical Pragmatics, pages 223–55. Academic Press. find
14. Riester, A., Lorenz, D., and Seemann, N. (2008). A semantic explication of information status and the underspecification of the recipients knowledge. In Proceedings of Sinn und Bedeutung, volume 12, pages 508–522. find
15. Riester, A., Lorenz, D., and Seemann, N. (2010). A recursive annotation scheme for referential information status. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC), pages 717–722. find
16. Rösiger, I. and Teufel, S. (2014). Resolving coreferent and associative noun phrases in scientific text. Proceedings of the Student Research Workshop of EACL 2014, page 45. find
17. Schäfer, U., Spurk, C., and Steffen, J. (2012). A fully coreference-annotated corpus of scholarly papers from the acl anthology. In Proceedings of the 24th International Conference on Computational Linguistics. International Conference on Computational Linguistics (COLING-2012), December 10-14, Mumbai, India, pages 1059–1070. find
18. Watson, R., Preiss, J., and Briscoe, T. (2003). The contribution of domain-independent robust pronominal anaphora resolution to open-domain question-answering. In Proceedings of the Symposium on Reference Resolution and its Applications to Question Answering and Summarization. Venice, Italy June, pages 23–25. find

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