---
title: "Mova: tree → frames — papers it applies — Elamur Research"
description: "20 papers Mova applies at the stage «tree → frames»: Reading the tree into frames — who did what to whom — with speech acts, hedges and coreference."
canonical: "https://research.elamur.ai/free/en/projects/mova/frames/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/projects/mova/frames/)

[home](https://md.research.elamur.ai/free/en/) / [projects](https://md.research.elamur.ai/free/en/projects/) / [Mova](https://md.research.elamur.ai/free/en/projects/mova/) / [Main list](https://md.research.elamur.ai/free/en/projects/mova/main/) / tree → frames

Mova · papers by stage

# tree → frames

Reading the tree into frames — who did what to whom — with speech acts, hedges and coreference. The 20 works of [Mova](https://mova.elamur.ai/free/en/)'s own list that this stage uses; measured marks a work whose effect Mova measured in its own experiments (8 here). Each title opens our card: the summary, how Mova uses the work, its references and who cites it. What the stage does is on [Mova's pipeline page](https://mova.elamur.ai/free/en/); every stage is on [the main list](https://md.research.elamur.ai/free/en/projects/mova/main/).

- [Politeness: Some Universals in Language Usage](https://md.research.elamur.ai/free/en/papers/brown-1987-politeness-some-universals-language-usage/) Penelope Brown, Stephen C. Levinson · 1987 · 10,545 citations **What Mova took:** `prag/data/cues.tsv` — a small hand-written cue list for the pragmatics crate; politeness markers (e.g. "please", apology and thanks cues) are grounded in this book, alongside Lakoff 1973 and Hyland 1998 for hedges and Searle for…
- [An Argument for Basic Emotions](https://md.research.elamur.ai/free/en/papers/ekman-1992-argument-basic-emotions/) Paul Ekman · 1992 · 9,900 citations **What Mova took:** `global/seeds/shortcuts/feelings.md`: the seed that maps event types to feelings…
- [Speech Acts: An Essay in the Philosophy of Language](https://md.research.elamur.ai/free/en/papers/searle-1969-speech-acts/) John R. Searle · 1969 · 6,673 citations **What Mova took:** `prag/data/cues.tsv` — the cue list's markers of illocutionary force (thanks, apologies, greetings, promises, warnings, suggestions, offers, yes/no) are compiled with this book (and Searle 1975 on indirect speech acts) as the…
- [Hedges: A Study in Meaning Criteria and the Logic of Fuzzy Concepts](https://md.research.elamur.ai/free/en/papers/lakoff-1973-hedges-study-meaning-criteria/) George Lakoff · 1973 · 1,486 citations **What Mova took:** `prag/data/cues.tsv` — the hedge entries in Mova's small hand-made cue list (sort of, kind of, maybe, I think and similar) take this paper, together with Hyland 1998, as their conceptual basis; the list itself is Mova's…
- [A Model-Theoretic Coreference Scoring Scheme](https://md.research.elamur.ai/free/en/papers/vilain-1995-model-theoretic-coreference-scoring-scheme/)measured Marc Vilain et al. · 1995 · 1,055 citations **What Mova took:** `coref/src/score.rs`: the MUC metric is implemented in Rust as one of the coreference scores, alongside B³, CEAF-e/CEAF-m, and CoNLL F1 (the average of MUC, B³ and CEAF-e).
- [An Algorithm for Pronominal Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/lappin-1994-algorithm-pronominal-anaphora-resolution/) Shalom Lappin, Herbert J. Leass · 1994 · 945 citations **What Mova took:** the development notes of `coref` ("What next") — the salience weights of this paper…
- [On Coreference Resolution Performance Metrics](https://md.research.elamur.ai/free/en/papers/luo-2005-coreference-resolution-performance-metrics/)measured Xiaoqiang Luo · 2005 · 855 citations **What Mova took:** `coref/src/score.rs` — Mova's own Rust scorer implements CEAF-e (φ4, entity-based) and CEAF-m (φ3, mention-based), with the optimal entity alignment found by Kuhn-Munkres, computed separately per connected component of the…
- [Hedging in Scientific Research Articles](https://md.research.elamur.ai/free/en/papers/hyland-1998-hedging-scientific-research-articles/)measured Ken Hyland · 1998 · 803 citations **What Mova took:** `prag/data/cues.tsv` — a small hand-made list of pragmatic cue words and phrases; the hedge entries (maybe, perhaps, probably, possibly, apparently, I think, I suppose, I guess…) are compiled with this book and Lakoff 1973 as…
- [Resolving Pronoun References](https://md.research.elamur.ai/free/en/papers/hobbs-1978-resolving-pronoun-references/)measured Jerry R. Hobbs · 1978 · 736 citations **What Mova took:** `coref/src/sieve.rs` — the candidate order for pronoun resolution follows the spirit of Hobbs: breadth-first, left-to-right tree traversal ordered by depth of the head and then position; first the mention's own clause, then the…
- [Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules](https://md.research.elamur.ai/free/en/papers/lee-2013-deterministic-coreference-resolution-based-entity/)measured Heeyoung Lee et al. · 2013 · 536 citations **What Mova took:** `coref/src/sieve.rs` — overall architecture: an ordered list of sieves from most to least precise…
- [A Multi-Pass Sieve for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/raghunathan-2010-multi-pass-sieve-coreference-resolution/)measured Karthik Raghunathan et al. · 2010 · 446 citations **What Mova took:** `coref/src/sieve.rs` — the overall architecture: an ordered list of sieves from most to least precise (speaker, exact, relaxed, appos, pred, relpron, acronym, reflexive, strict head-match variants, proper_head, pronoun), each…
- [Algorithms for Scoring Coreference Chains](https://md.research.elamur.ai/free/en/papers/bagga-1998-algorithms-scoring-coreference-chains/)measured Amit Bagga, Breck Baldwin · 1998 · 325 citations **What Mova took:** `coref/src/score.rs` — the coreference scorer implements B³ alongside MUC, CEAF-e and CEAF-m; the CoNLL F1 reported for Mova's coreference resolver is the mean of MUC, B³ and CEAF-e.
- [Scoring Coreference Partitions of Predicted Mentions: A Reference Implementation](https://md.research.elamur.ai/free/en/papers/pradhan-2014-scoring-coreference-partitions-predicted-mentions/)measured Sameer Pradhan et al. · 2014 · 284 citations **What Mova took:** `coref/src/score.rs` — the MUC, B-cubed, CEAF-e and CEAF-m formulas for predicted mentions follow this paper: no mention manipulation, unmatched mentions just do not contribute; CoNLL F1 is the mean of MUC, B-cubed and CEAF-e…
- [Simple Coreference Resolution with Rich Syntactic and Semantic Features](https://md.research.elamur.ai/free/en/papers/haghighi-2009-simple-coreference-resolution-rich-syntactic/) Aria Haghighi, Dan Klein · 2009 · 277 citations **What Mova took:** the development notes of `coref` and `coref/src/sieve.rs`: Mova's coreference module is a deterministic multi-pass sieve (architecture after Raghunathan et al. 2010 and Lee et al. 2013). From this paper it takes the principle…
- [Udapi: Universal API for Universal Dependencies](https://md.research.elamur.ai/free/en/papers/popel-2017-udapi-universal-api-universal-dependencies/) Martin Popel, Zdeněk Žabokrtský, Martin Vojtek · 2017 · 61 citations **What Mova took:** `coref/src/score.rs` and `coref/src/corefud.rs` — the head of a mention span is computed as in Udapi's `corefud.MoveHead` block: the word whose own head lies outside the span; among several candidates, the highest in the tree…
- [CorefUD 1.0: Coreference Meets Universal Dependencies](https://md.research.elamur.ai/free/en/papers/nedoluzhko-2022-corefud-1-0-coreference-meets/) Anna Nedoluzhko et al. · 2022 · 48 citations **What Mova took:** `coref` — `coref resolve` writes its output in the CorefUD format: `Entity=` annotations in MISC with a `# global.Entity = eid-etype-head-other` header, where `head` is the position of the head inside the span and `other` records…
- [CogNIAC: high precision coreference with limited knowledge and linguistic resources](https://md.research.elamur.ai/free/en/papers/baldwin-1997-cogniac-high-precision-coreference-limited/) Breck Baldwin · 1997 · 31 citations **What Mova took:** the development notes of `coref`, sieve `speaker`: the rules for first- and second-person pronouns within one voice…
- [CogNIAC: A Discourse Processing Engine](https://md.research.elamur.ai/free/en/papers/baldwin-1995-cogniac-discourse-processing-engine/) Breck Baldwin · 1995 · 31 citations **What Mova took:** `coref/src/sieve.rs` (`find_quote_authors`) — determining who speaks in a quotation: in a sentence containing a quote, the author is the subject of a speech verb outside the quotation marks; speech verbs come from a closed…
- [Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches?](https://md.research.elamur.ai/free/en/papers/novak-2025-findings-fourth-shared-task-multilingual/) Michal Novák et al. · 2025 · 10 citations **What Mova took:** `coref/src/score.rs` — mention matching by head, as in the shared task's primary metric: gold and system mentions match when they share a head; several mentions with the same head are disambiguated by span…
- [Findings of the Fifth Shared Task on Multilingual Coreference Resolution: Expanding Datasets for Long-Range Entities](https://md.research.elamur.ai/free/en/papers/novak-2026-findings-fifth-shared-task-multilingual/) Michal Novák et al. · 2026 · 6 citations **What Mova took:** `coref/src/score.rs` — together with the 2025 edition, the source for head-based mention matching as the primary scoring mode (CRAC 2023–2026 convention).