---
title: "Revisiting the Givenness Hierarchy. A Corpus-Based Evaluation"
description: "The study offers a scalable, reproducible test for a widely cited theory, shows how coreference data can… 48 references, cited by 1 paper here."
authors: ["Christian Chiarcos"]
year: 2025
venue: "Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference"
source: "https://aclanthology.org/2025.crac-1.3/"
doi: "10.18653/v1/2025.crac-1.3"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/chiarcos-2025-revisiting-givenness-hierarchy-corpus-based/"
---
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# Revisiting the Givenness Hierarchy. A Corpus-Based Evaluation

**Authors:** [Christian Chiarcos](https://md.research.elamur.ai/free/en/authors/christian-chiarcos/) · **Year:** 2025 · **Venue:** [Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference](https://md.research.elamur.ai/free/en/venues/crac/) ([CRAC 2025](https://md.research.elamur.ai/free/en/venues/crac/2025/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2025.crac-1.3/) · [PDF](https://aclanthology.org/2025.crac-1.3.pdf) · [DOI 10.18653/v1/2025.crac-1.3](https://doi.org/10.18653/v1/2025.crac-1.3) · [OpenAlex](https://openalex.org/W4416037546)

**Citations:** 0 citations (OpenAlex, 2026-10-14) · 1 in our library, of the 149,439 papers whose bibliographies we read

## Summary
The Givenness Hierarchy (GH) of Gundel et al. (1993) links six cognitive statuses of a referent, ranging from *in focus* to *type identifiable*, to the forms speakers use for it: zero, pronoun, demonstrative, definite or indefinite NP. Its evidence so far came from small elicitation studies whose annotations are not public and whose counts often miss statistical significance. Chiarcos instead infers the statuses automatically from existing coreference corpora, which together span every one of the seven languages examined in the original GH work: the European languages English, Spanish and Russian, along with Arabic and Chinese, plus Japanese and Korean. Some corpora come from CorefUD; for the others, UD parses were produced with spaCy or UDPipe. The status rules follow the 2006 GH annotation guidelines but use only criteria that ignore the surface form, to avoid circular reasoning. Across languages, the predicted form–status associations largely hold. However, UNIQUE cannot be approximated reliably, and demonstrative NPs fit the theory poorly. The study offers a scalable, reproducible test for a widely cited theory, shows how coreference data can bootstrap GH labels, and releases scripts that convert Japanese and Korean corpora to the CorefUD format.

## Key points
- Gundel et al.'s English elicitation counts were re-analysed with Pearson correlation and binary χ² per form–status pair. The core pairings came out significant (in focus–pronoun, unique–definite NP, type–indefinite NP), but data on demonstratives and emphatic pronouns were too sparse to judge.
- The guidelines contain 15 criteria: 6 are directly implementable, 6 can be approximated, and 3 are not covered. Surface cues could reach about 80% coverage, but only 9 form-independent criteria (60%) were used.
- Operational choices: an utterance is treated as a sentence, "mentioned" means having an annotated antecedent or anaphor, and *in focus* is approximated by the UD `nsubj` of the preceding sentence.
- Several corpus biases affect the results:
  - OntoNotes and ParCorFull mark only specific referents, so the type status is missing.
  - KoCoNovel covers protagonists only.
  - The Russian and Korean data lack zero anaphora.
  - No corpus annotates event anaphora.
  - NTC 1.5 (Japanese) has missing text boundaries.
- The author proposes merging *unique* and *referential* into a single status, XREF, in future GH implementations.

## Interesting ideas
- To test whether forms predict a category, label the category only from evidence that does not inspect those forms; otherwise the evaluation confirms itself.
- Instead of trusting raw tables in a paper, recompute per-cell correlation and χ² significance before accepting a claimed pattern.
- Treat givenness as an ordered, implicative scale and assign the highest status that applies, using simple recency windows: subject of the previous sentence, or mentioned in the last one or two sentences.
- The same status-to-form mapping can work in reverse, choosing pronoun, definite or indefinite NP based on how given a referent currently is.
- When a distinction cannot be recovered reliably from the data, merge the categories (as with XREF) rather than keep a noisy split.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (learn): when silver labels are used to validate a module, derive them from signals independent of the features under test, as a built-in guard against circular evaluation.
- **I2** (learn): run per-category significance checks against negative controls before adopting a rule or a reported regularity.
- **I3** (frames): coreference could tag each mention with an explainable givenness status from these window rules, then use the status to rank antecedent candidates.
- **I4** (back): text generation from the meaning graph could pick referring expressions by the referent's computed status instead of always repeating full names.
- **I5** (world): entity-status attributes in the world model could use coarser classes wherever the evidence cannot separate finer ones.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [University of Augsburg](https://md.research.elamur.ai/free/en/universities/university-of-augsburg/) — University, Augsburg, Germany · 8 works · 38,342 citations

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## Cite

Cite as: Christian Chiarcos. 2025. Revisiting the Givenness Hierarchy. A Corpus-Based Evaluation. Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference.

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

```bibtex
@inproceedings{chiarcos2025revisiting,
  title = {{Revisiting the Givenness Hierarchy. A Corpus-Based Evaluation}},
  author = {Christian Chiarcos},
  booktitle = {Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference},
  year = {2025},
  doi = {10.18653/v1/2025.crac-1.3},
  url = {https://doi.org/10.18653/v1/2025.crac-1.3}
}
```

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*Updated 1 November 2026*