Papers with semantic annotation
The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation (C18-2)
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| Challenge: | INCEpTION is an annotation platform for interactive and semantic annotation . the platform is both generic and modular . |
| Approach: | INCEpTION is an annotation platform for interactive and semantic annotation . the platform incorporates machine learning capabilities which actively assist annotators . |
| Outcome: | INCEpTION is an open-source annotation platform for tasks including interactive and semantic annotation. |
LiDARR: Linking Document AMRs with Referents Resolvers (2025.acl-demo)
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Jon Cai, Kristin Wright-Bettner, Zekun Zhao, Shafiuddin Rehan Ahmed, Abijith Trichur Ramachandran, Jeffrey Flanigan, Martha Palmer, James Martin
| Challenge: | Abstract Meaning Representation (AMR) is a formalism for semantic representation of natural language text. |
| Approach: | They propose a web tool for semantic annotation at the document level using Abstract Meaning Representation (AMR) it integrates an AMR-to-surface alignment model and a coreference resolution model into the tool . |
| Outcome: | The proposed tool simplifies the creation of knowledge graphs from natural language documents . it integrates an AMR-to-surface alignment model and coreference resolution model . |
The ISO Standard for Dialogue Act Annotation, Second Edition (2020.lrec-1)
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Harry Bunt, Volha Petukhova, Emer Gilmartin, Catherine Pelachaud, Alex Fang, Simon Keizer, Laurent Prévot
| Challenge: | ISO standard 24617-2 for dialogue act annotation has been used in corpus annotation and in the design of components for spoken and multimodal interactive systems. |
| Approach: | ISO standard 24617-2 for dialogue act annotation is proposed for a second edition . this second edition allows a more accurate annotation of dependence relations and rhetorical relations in dialogue. |
| Outcome: | The proposed second edition of ISO 24617-2 for dialogue act annotation addresses some inaccuracies and undesirable limitations. |
Effective QA-Driven Annotation of Predicate–Argument Relations Across Languages (2026.eacl-long)
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| Challenge: | Explicit representations of predicate-argument relations are a cornerstone of natural language understanding. |
| Approach: | They propose a cross-linguistic projection approach that reuses an English QA-SRL parser within a constrained translation and word-alignment pipeline to automatically generate question-answer annotations aligned with target-language predicates. |
| Outcome: | The proposed approach outperforms strong multilingual LLMs in Hebrew, Russian, and French. |
GeCzLex: Lexicon of Czech and German Anaphoric Connectives (2020.lrec-1)
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| Challenge: | Existing lexicons of connectives are interlinked with each other to provide a bilingual inventory of connective entries. |
| Approach: | They introduce the first version of a lexicon for translation equivalents of Czech and German discourse connectives. |
| Outcome: | The lexicon is the first bilingual inventory of connectives with linkage on the level of individual entries. |
Unsupervised Mapping of Arguments of Deverbal Nouns to Their Corresponding Verbal Labels (2023.findings-acl)
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| Challenge: | Deverbal nouns are nominal forms of verbs used in English texts to describe events or actions . many NLP systems neglect to handle nominalized constructions, resulting in limited applications . |
| Approach: | They propose to map arguments of deverbal nouns to universal-dependency relations of verbal constructions . they propose to use the same labels as verbal cases to map the arguments . |
| Outcome: | The proposed approach maps arguments of nominalized nouns to the corresponding verbal constructions. |
Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities (N19-1)
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Alexander Erdmann, David Joseph Wrisley, Benjamin Allen, Christopher Brown, Sophie Cohen-Bodénès, Micha Elsner, Yukun Feng, Brian Joseph, Béatrice Joyeux-Prunel, Marie-Catherine de Marneffe
| Challenge: | Scholars in interdisciplinary fields like the Digital Humanities are increasingly interested in semantic annotation of specialized corpora. |
| Approach: | They propose an active learning solution for named entity recognition that maximizes a custom model’s improvement per additional unit of manual annotation. |
| Outcome: | The proposed model reduces required annotation by 20-60% and outperforms a competitive active learning baseline. |
Simple Semantic Annotation and Situation Frames: Two Approaches to Basic Text Understanding in LORELEI (L18-1)
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| Challenge: | Existing annotations for low resource languages are under-resourced for human language technology, but lack of resources does not correlate with lack of need for such technologies. |
| Approach: | They propose two types of semantic annotation for the DARPA Low Resource Languages for Emerging Incidents program: Simple Semantic Annotation (SSA) and Situation Frames (SF). |
| Outcome: | The proposed approaches are aimed at labeling basic semantic information relevant to humanitarian aid and disaster relief scenarios. |
Towards an ISO Standard for the Annotation of Quantification (L18-1)
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| Challenge: | Quantification occurs in every sentence of written text or spoken discourse because application of a predicate to one or more sets of objects gives rise to questions of relative scope, of cardinality, and of distribution (or 'distributivity') of the predicacy over the sets of arguments. |
| Approach: | They propose an approach to the annotation of quantification that is being developed as part of an effort by the International Organisation for Standardisation ISO to define interoperable semantic annotation schemes. |
| Outcome: | The proposed scheme includes both count and mass NP quantifiers, as well as NPs with syntactically and semantically complex heads with internal quantification and scoping structures. |
Quantification Annotation in ISO 24617-12, Second Draft (2022.lrec-1)
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Harry Bunt, Maxime Amblard, Johan Bos, Karën Fort, Bruno Guillaume, Philippe de Groote, Chuyuan Li, Pierre Ludmann, Michel Musiol, Siyana Pavlova, Guy Perrier, Sylvain Pogodalla
| Challenge: | a project aimed at establishing an interoperable annotation schema for quantification phenomena was relaunched in early 2022 due to the Covid-19 pandemic . |
| Approach: | This paper describes the continuation of a project that aims at establishing an interoperable annotation schema for quantification phenomena as part of the ISO suite of semantic annotation standards. |
| Outcome: | The proposed schema is part of the ISO suite of semantic annotation standards known as the Semantic Annotation Framework (SemAF). |
Aligning Images and Text with Semantic Role Labels for Fine-Grained Cross-Modal Understanding (2022.lrec-1)
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| Challenge: | Currently, image retrieval systems can retrieve relevant results for diverse inputs, but they do not provide a way to intentionally inject variety into the search results. |
| Approach: | They propose a multimodal dataset that combines semantic annotations with image bounding boxes. |
| Outcome: | The proposed system improves image retrieval performance and flexibility. |
Controlled Crowdsourcing for High-Quality QA-SRL Annotation (2020.acl-main)
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Paul Roit, Ayal Klein, Daniela Stepanov, Jonathan Mamou, Julian Michael, Gabriel Stanovsky, Luke Zettlemoyer, Ido Dagan
| Challenge: | Question-answer driven Semantic Role Labeling (QA-SRL) is an open and natural flavour of SRL, potentially attainable from laymen. |
| Approach: | They propose a question-answer driven semantic role labeling approach that uses question-announced questions to label predicate-argument relationships. |
| Outcome: | The proposed method yields high-quality annotation with dramatically higher coverage, enabling future replicable research of natural semantic annotations. |
Cross-lingual and Cross-domain Evaluation of Machine Reading Comprehension with Squad and CALOR-Quest Corpora (2020.lrec-1)
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| Challenge: | a recent study has shown that language mismatch and domain mismatch can affect performance of a machine reading task . a factor between language mismatched and domain-mismatched has the strongest influence on performance . |
| Approach: | They compare the cross-language and cross-domain capabilities of BERT on a machine reading comprehension task on two corpora: SQuAD and a new French Machine Reading dataset. |
| Outcome: | The proposed model matches human performance on a machine reading comprehension task with BERT on Chinese and French documents with interesting results. |
A linguistically-motivated evaluation methodology for unraveling model’s abilities in reading comprehension tasks (2024.emnlp-main)
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| Challenge: | Existing models fail for linguistic characteristics of input examples, despite the impressive quantity of scientific studies dedicated to them, the capabilities, limitations, and risks of these models remain largely unknown. |
| Approach: | They propose to use semantic frame annotation to characterize examples by a small number of complexity factors to account for model’s difficulty. |
| Outcome: | The proposed evaluation methodology is based on the intuition that certain examples consistently yield lower scores regardless of model size or architecture. |
Towards Semantic Tagging for Irish (2024.lrec-main)
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| Challenge: | well annotated corpora have been shown to have great value in linguistic and non-linguistic research . minority languages suffer from fewer available language resources than majority languages . a new method for evaluation of semantic annotation is being developed for Irish . |
| Approach: | They propose to build a tool-set for semantic annotation of Irish using semantic tags . they propose to use a lexicon built from a variety of sources to evaluate the tool . |
| Outcome: | a new method for evaluation of semantic annotation has been developed for Irish . the proposed method has 90% lexical coverage and almost 80% accuracy . |