Papers by Francis Bond

11 papers
ChainNet: Structured Metaphor and Metonymy in WordNet (2024.lrec-main)

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Challenge: In a typical lexicon, word senses are encoded as a list, without inter-sense relations.
Approach: They propose a lexical resource which explicitly identifies the senses of a word's senses by expressing how they are derived from one another.
Outcome: The proposed resource expresses how senses in the Open English Wordnet are derived from one another.
Commonsense inference in human-robot communication (D19-60)

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Challenge: a gap exists in natural language understanding of commands between humans and machines.
Approach: They propose a method for commonsense inference to transform high-level commands into action commands for robotic systems to execute.
Outcome: The proposed method allows to build a knowledge base that consists of a large set of commonsense inferences.
Singlish Where Got Rules One? Constructing a Computational Grammar for Singlish (2022.lrec-1)

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Challenge: Singlish is a variety of English spoken in Singapore and has many non-standard features.
Approach: They propose to use Singlish as a branch of English grammar to implement new rules and add new lexical types to it.
Outcome: The proposed grammar is based on the existing rules and lexical types from the English resource grammar and compared with the standard English grammar.
Toward An Epic Epigraph Graph (L18-1)

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Challenge: a database of epigraphs is being developed to reveal literary influence as a set of connections between authors over time.
Approach: a database of epigraphs is created to map literary influence as a set of connections between authors . the database is being developed under an open license .
Outcome: a database of epigraphs is being developed to reveal literary influence over time . the database includes epigraph quotations from over 12,000 literary works . authors use epigraph to set theme and link work to existing body of literature .
More Aligned, Less Diverse? Analyzing the Grammar and Lexicon of Two Generations of LLMs (2026.acl-long)

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Challenge: a growing number of studies compare LLMs with human-authored text . diversity is unclear, but it is important to understand what makes human and machine writing distinct .
Approach: They compare syntactic properties of AI-generated and human-authored English news texts . they use the Head-Driven Phrase Structure Grammar and the English Resource Grammar .
Outcome: The proposed model differs from human-authored English news text in two years.
Comparing LLM-generated and human-authored news text using formal syntactic theory (2025.acl-long)

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Challenge: a systematic comparison of LLM-generated and human-authored texts is a topic of growing interest in the field of natural language processing.
Approach: They compare LLM-generated and human-authored New York Times texts using a formal syntactic theory . they use a broad-coverage English resource grammar to analyze the texts .
Outcome: The proposed comparisons reveal systematic differences between human and LLM-generated texts . the authors hope the results will lead to further discoveries about grammatical properties of LLMs .
Linking the TUFS Basic Vocabulary to the Open Multilingual Wordnet (2020.lrec-1)

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Challenge: The TUFS Basic Vocabulary Modules are hand created, using commonly occurring vocabulary.
Approach: They propose to link the TUFS Basic Vocabulary Modules with the Open Multilingual Wordnet to create a multilingual lexicon.
Outcome: The proposed lexicons can be used to evaluate existing wordnets, add data to wordnet synsets and create new open wordnet for Khmer, Korean, Lao, Mongolian, Russian, Tagalog, Urdua nd Vietnamese.
Some Issues with Building a Multilingual Wordnet (2020.lrec-1)

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Challenge: Notable extensions include: confidence, corpus frequency, orthographic variants, lexicalized and non-lexicalised synsets and lemmas, new parts of speech, and more.
Approach: They propose to integrate a new open multilingual wordnet format that tests the extensions introduced by the new format and integrates a set of tools to ensure the integrity of the Collaborative Interlingual Index.
Outcome: The proposed format integrates a set of tools that test the extensions while ensuring the integrity of the Collaborative Interlingual Index (CILI).
The Tembusu Treebank: An English Learner Treebank (2022.lrec-1)

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Challenge: a new treebank is created to help diagnose ungrammatical sentences using mal-rules . the Tembusu Learner Treebank is an open treebank created from the corpus of Learner English .
Approach: They propose to use the Tembusu Learner Treebank to train a new parse-ranking model for the English Resource Grammar . the model incorporates mal-rules in the annotation of ungrammatical sentences .
Outcome: The Tembusu Learner Treebank is an open treebank created from the NTU Corpus of Learner English . the treebank is unique for incorporating mal-rules in the annotation of ungrammatical sentences .
Automated Writing Support Using Deep Linguistic Parsers (2020.lrec-1)

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Challenge: Automated Grammar Error Detection (GED) and Grammar Erreor Correction (GEC) are tasks that have attracted some attention within the NLP community.
Approach: They propose a web-based system that integrates English Grammatical Error Detection (GED) and course-specific stylistic guidelines to automatically review and provide feedback on student assignments.
Outcome: The system integrates both general NLP methods and high precision parsers to check student assignments before they are submitted for grading.
Sense and Sentiment (2022.lrec-1)

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Challenge: Existing sentiment lexicons and concept-based sentiment-tagged corpora are not accurate, and it is difficult to map sentiment scores accurately to different languages.
Approach: They examine existing sentiment lexicons and sense-based sentiment-tagged corpora to find out how sense and concept-based semantic relations effect sentiment scores.
Outcome: The proposed lexicon can be used to generate sentiment lexicos for English using the Open Multilingual Wordnet.

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