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# Toward Givenness Hierarchy Theoretic Natural Language Generation

**Authors:** Poulomi Pal and Tom Williams · **Year:** 2020 · **Venue:** arXiv:2007.16009 **Link:** [arxiv.org/abs/2007.16009](https://arxiv.org/abs/2007.16009) · **Licence:** arXiv non-exclusive distribution licence — summary only

[**0** citations](https://openalex.org/works?filter=cites:W3046251652) openalex · 2026-10-18[arXiv:2007.16009](https://openalex.org/S4306400194)[licence](http://arxiv.org/licenses/nonexclusive-distrib/1.0/)

- [Publisher's page](https://arxiv.org/abs/2007.16009)
- [PDF](https://arxiv.org/pdf/2007.16009)
- [arXiv 2007.16009](https://arxiv.org/abs/2007.16009)
- [OpenAlex](https://openalex.org/W3046251652)

**Authors (2)**

1. Poulomi Pal
2. [Tom Williams](https://openalex.org/A5101736923) [ORCID](https://orcid.org/0000-0001-7921-771X) · h 26 · 2203 citations · 170 works

Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart.

## What it is about

A robot that talks with people must choose between *it*, *this N*, *that N* and *the N*. The Givenness Hierarchy (GH) says that the form reflects the cognitive status a referent has in the hearer's mind: in focus, activated, familiar, uniquely identifiable, referential, type identifiable. Earlier work used GH data structures to understand anaphora. This paper addresses generation. It proposes a per-entity Bayesian filter that keeps a distribution over three statuses (in focus, activated, familiar), updated by how each mention is used (not mentioned, mentioned in a non-topic role, mentioned as topic). It also gives a Describe algorithm that picks a form from the status, uses only same-or-higher-status entities as distractors, and adjusts the form for distance. No experiment is reported; the authors plan a human study of preferred referring forms.

## Ideas

- I1. A count-based status tracker: per entity, a state among the three statuses, changed by a fixed transition table keyed on the grammatical role of the mention (subject or topic moves to in focus; object to activated; others to familiar). Store the table in a BTreeMap so updates are deterministic.
- I2. Form rule: choose *it* if the entity is in focus with no competing distractor, *this N* if activated, *that N* if familiar, and *the N* otherwise. Check the rule against the pronoun and demonstrative choices in Mova's own coreference data.
- I3. Narrow the distractor set by status: only entities of the same or higher status need ruling out. This shrinks the candidate set checked in `coref/src/sieve.rs`.
- I4. Negative control: a random status assignment must give worse form accuracy than the tracker.

## For Mova

Chapter: [35. Reference and coreference](https://md.mova.elamur.ai/free/en/docs/languages/en/35-reference-and-coreference/), and [12. Pronouns, determiners and numerals](https://md.mova.elamur.ai/free/en/docs/languages/en/12-pronouns-determiners-numerals/) for the forms. Code: `coref/src/sieve.rs` and `coref/src/mention.rs`. Measure: form accuracy (pronoun, demonstrative, definite) on a held-out set of Mova texts, and the mean number of distractors checked per mention; two runs must match.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [arXiv 2007.16009](https://arxiv.org/abs/2007.16009)

```
@misc{pal2020toward,
  title = {{Toward Givenness Hierarchy Theoretic Natural Language Generation}},
  author = {Pal, Poulomi and Williams, Tom},
  year = {2020},
  eprint = {2007.16009},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2007.16009}
}
```

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## References

2 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Arnold, J. E. (2016). Explicit and emergent mechanisms of information status. Topics in Cog. Sci.. [find](https://scholar.google.com/scholar?q=Arnold%2C+J%2E+E%2E+%282016%29%2E+Explicit+and+emergent+mechanisms+of+information+status%2E+Topics+in+Cog%2E+Sci%2E%2E)
2. Callaway, C. B., & Lester, J. C. (2002). Pronominalization in generated discourse and dialogue. Proc. ACL (pp. 88–95). [find](https://scholar.google.com/scholar?q=Callaway%2C+C%2E+B%2E%2C+%26+Lester%2C+J%2E+C%2E+%282002%29%2E+Pronominalization+in+generated+discourse+and+dialogue%2E+Proc%2E+ACL+%28pp%2E+88%E2%80%9395%29%2E)