Liane Guillou
Liane Guillou wrote 2 of the papers Mova reads, in 2017–2022, most of them on Coreference resolution, Semantic role labeling, Machine translation; often with Chantal Amrhein, Christian Hardmeier, Nikita Moghe.
OpenAlex · ORCID · h-index 11 · 492 citations · 62 works — openalex, 2026-10-18
Topics: Coreference resolution 1 · Semantic role labeling 1 · Machine translation 1
Ideas Mova took (1)
- kept — Classify every it three ways before the pronoun sieve runs, with rules from the paper's strongest cues, and let only the anaphoric ones reach nominal antecedents. (What is it? Disambiguating the different readings of the… · coref: «it» pleonastic/event/anaphoric before the pronoun sieve; GUM dev CoNLL gold 75.18/64.30→75.21/64.32, SLM trees 69.70/57.57→69.82/57.66, «it» precision…)
Papers
- ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics (2022)
ACES is a challenge set of about 36,500 contrastive examples over 146 language pairs and 68 phenomena. The phenomena come from the accuracy branch of the MQM ontology, extended with classes such as real-world knowledge and wrong language, from perturbations of characters and tokens up to discourse errors. Each… - What is it? Disambiguating the different readings of the pronoun 'it' (2017)
1 idea kept
English it can be anaphoric to a noun phrase («I have a bicycle. It is red»), event-referring to a verb phrase, clause or sentence («He lost his job. It came as a total surprise»), or pleonastic («It is raining»). Using 2,506 instances of it from the ParCor and DiscoMT corpora (52% anaphoric, 33% event, 15%…
Co-authors (4)
- Chantal Amrhein
- Christian Hardmeier
- Nikita Moghe
- Sharid Loáiciga
This page in Markdown → https://md.mova.elamur.ai/free/en/docs/papers/authors/liane-guillou/