[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/lingbulk-2020-khullar-finding-right-one-resolving-it/) [home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [English](https://md.mova.elamur.ai/free/en/docs/papers/en/) / Finding The Right One and Resolving it # Finding The Right One and Resolving it **Authors:** [Payal Khullar](https://md.mova.elamur.ai/free/en/docs/papers/authors/payal-khullar/), Arghya Bhattacharya and [Manish Shrivastava](https://md.mova.elamur.ai/free/en/docs/papers/authors/manish-shrivastava/) · **Year:** 2020 · **Venue:** Proceedings of the 24th Conference on Computational Natural Language Learning (CoNLL 2020) **Link:** [aclanthology.org/2020.conll-1.10](https://aclanthology.org/2020.conll-1.10/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) [**1** citations](https://openalex.org/works?filter=cites:W3098812086) openalex-snapshot · 2026-10-14[**1** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lingbulk-2020-khullar-finding-right-one-resolving-it/) of the 140673 papers whose bibliographies we read[Proceedings of the 24th Conference on Computational Natural Language Learning](https://aclanthology.org/volumes/2020.conll-1/)[licence](https://creativecommons.org/licenses/by/4.0/) - [Publisher's page](https://aclanthology.org/2020.conll-1.10/) - [PDF](https://aclanthology.org/2020.conll-1.10.pdf) - [DOI 10.18653/v1/2020.conll-1.10](https://doi.org/10.18653/v1/2020.conll-1.10) - [OpenAlex](https://openalex.org/W3098812086) **Authors (3)** 1. [Payal Khullar](https://openalex.org/A5006065835) [Semantic Scholar](https://www.semanticscholar.org/author/51124702) · h 3 · 45 citations · 7 works 2. [Arghya Bhattacharya](https://openalex.org/A5009865031) [ORCID](https://orcid.org/0000-0002-0557-4340) · [Semantic Scholar](https://www.semanticscholar.org/author/9177399) · h 4 · 56 citations · 25 works 3. [Manish Shrivastava](https://openalex.org/A5013675579) [ORCID](https://orcid.org/0000-0001-8705-6637) · [Semantic Scholar](https://www.semanticscholar.org/author/2045067) · h 26 · 2281 citations · 205 works Citations and author metrics from openalex-snapshot (2026-10-14); authors with the same name are not always told apart. ## What it is about One-anaphora is the use of the word "one" or "ones" for a noun head, as in "the black one". The paper separates it from the determinative use of "one" as a numeral, a confusion that has weakened earlier computational work. The authors annotate one-anaphora with their antecedents in the British National Corpus and release a gold corpus of 921 instances. Template rules over POS strings, run on spaCy parses, reach 78.34% precision, 85.92% recall and 81.96% F1 for detection. Neural classifiers with fastText and BERT embeddings are then trained on the corpus. From the templates, 15,647 BNC sentences contain 18,669 one-anaphora words, so the sentence-level rate is 6.25%, far below the 12–15% reported in earlier annotation efforts. ## Ideas - I1. `en/src/expert.rs`: a deterministic detector for "one" and "ones" that uses the UD labels to tell the nominal head from the numeral. Report precision and recall on the 921-instance corpus, test only, since the BNC is NC. - I2. Determinative split: count how many "one" tokens on EWT test are numerals (det with a number reading) and how many are nominal heads. The paper's point is that mixing the two inflates the counts, so the split should be reported first. - I3. Coreference hook: link a one-anaphor to the nearest noun head with compatible modifiers, using the candidate set of the `coref` crate. Measure resolution accuracy on the test part only, and report the paper's own baseline next to it. ## For Mova The code is `en/src/expert.rs`, `coref` and `en/src/ctx.rs`. The chapters are [35. Reference and coreference](https://md.mova.elamur.ai/free/en/docs/languages/en/35-reference-and-coreference/) and [22. Phrases: noun, adjective, adverb and prepositional phrases](https://md.mova.elamur.ai/free/en/docs/languages/en/22-phrases/). The gold corpus comes from the NC BNC, so it is for measurement only. Measure first: the detector against the gold corpus, with the determinative split reported. Topics: [Coreference resolution](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/) ## Cite The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/2020.conll-1.10](https://doi.org/10.18653/v1/2020.conll-1.10) ``` @inproceedings{khullar2020finding, title = {{Finding The Right One and Resolving it}}, author = {Khullar, Payal and Bhattacharya, Arghya and Shrivastava, Manish}, booktitle = {Proceedings of the 24th Conference on Computational Natural Language Learning}, year = {2020}, doi = {10.18653/v1/2020.conll-1.10}, url = {https://doi.org/10.18653/v1/2020.conll-1.10} } ``` - [← previous AMALGUM – A Free, Balanced, Multilayer English Web Corpus](https://md.mova.elamur.ai/free/en/docs/papers/lingbulk-2020-gessler-amalgum-free-balanced-multilayer-english/) - [next → Pattern Dictionary of English Prepositions](https://md.mova.elamur.ai/free/en/docs/papers/litkowski-2014-pattern-dictionary-english-prepositions/) - [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/) ## References 4 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. Nameera Akhtar, Maureen Callanan, Geoffrey K Pullum, and Barbara C Scholz. 2004. Learning antecedents for anaphoric one. Cognition, 4:141–145. 65.49 64.22 78.87 79.35 71.74 89.35 71.76 67.77 83.78 55.24 58.97 63.07 61.29 65.74 72.33 58.11 62.17 67.38 [find](https://scholar.google.com/scholar?q=Nameera+Akhtar%2C+Maureen+Callanan%2C+Geoffrey+K+Pullum%2C+and+Barbara+C+Scholz%2E+2004%2E+Learning+antecedents+for+anaphoric+one%2E+Cognition%2C+4%3A141%E2%80%93145%2E+65%2E49+64%2E22+78%2E87+79%2E35+71%2E74+89%2E35+71%2E76+67%2E77+83%2E78+55%2E) 2. Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2016. Enriching word vectors with subword information. arXiv preprint arXiv:1607.04606. 59.99 70.01 64.61 [find](https://scholar.google.com/scholar?q=Piotr+Bojanowski%2C+Edouard+Grave%2C+Armand+Joulin%2C+and+Tomas+Mikolov%2E+2016%2E+Enriching+word+vectors+with+subword+information%2E+arXiv+preprint+arXiv%3A1607%2E04606%2E+59%2E99+70%2E01+64%2E61) 3. Joan Bresnan. 1971. A note on the notion “identity of sense anaphora”. Linguistic Inquiry, 2:589–597. [find](https://scholar.google.com/scholar?q=Joan+Bresnan%2E+1971%2E+A+note+on+the+notion+%E2%80%9Cidentity+of+sense+anaphora%E2%80%9D%2E+Linguistic+Inquiry%2C+2%3A589%E2%80%93597%2E) 4. Carl Lee Baker. 1978. Introduction to generative transformational syntax. Englewood Cliffs, NJ:: Prentice-Hal. [find](https://scholar.google.com/scholar?q=Carl+Lee+Baker%2E+1978%2E+Introduction+to+generative+transformational+syntax%2E+Englewood+Cliffs%2C+NJ%3A%3A+Prentice%2DHal%2E)