Papers by Martha Palmer
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 . |
GLEN: General-Purpose Event Detection for Thousands of Types (2023.emnlp-main)
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| Challenge: | ACE 2005 2 is the first large-scale event extraction dataset with 205K event mentions and 3,465 different types. |
| Approach: | They propose to use the DWD Overlay to map PropBank rolesets to a large distantlysupervised training dataset with partial labels to make event extraction more accessible. |
| Outcome: | The proposed model performs better than baselines including InstructGPT and ACE 2005 2 despite being 18 years old . key limitations of ACE include its small event ontology of 33 types, small dataset size of around 600 documents and restricted domain (with a significant portion concentrated on military conflicts). |
What Would a Teacher Do? Predicting Future Talk Moves (2021.findings-acl)
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| Challenge: | Recent advances in natural language processing (NLP) have the ability to transform how classroom learning takes place. |
| Approach: | They propose a task that uses the academically productive talk framework to learn strategies that make for the best learning experience. |
| Outcome: | The proposed task outperforms baselines on academically productive talk (FTMP) and shows that it outperformed human performance on FTMP. |
A Graphical Interface for Curating Schemas (2021.acl-demo)
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| Challenge: | Existing work on analyzing information extracted from documents has focused on examining the model understanding of complex schemas. |
| Approach: | They propose a curation interface that takes an IE system’s output in a pre-defined format and generates a graphical representation of its elements. |
| Outcome: | The proposed interface can be used to edit and prune schemas for complex events like Improvised Explosive Device (IED) based scenarios. |
In Search of the Lost Arch in Dialogue: A Dependency Dialogue Acts Corpus for Multi-Party Dialogues (2025.findings-acl)
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Jon Cai, Brendan King, Peyton Cameron, Susan Windisch Brown, Miriam Eckert, Dananjay Srinivas, George Arthur Baker, V Kate Everson, Martha Palmer, James Martin, Jeffrey Flanigan
| Challenge: | Understanding speaker intentions remains a challenge in NLP . a number of corpora annotated using theoretical frameworks of dialogue focus on utterance-level labeling of speaker intent, missing wider context, or the rhetorical structure of a dialogue. |
| Approach: | They propose to annotate a corpus of 33 dialogues and over 9,000 utterance units using the Dependency Dialogue Acts framework. |
| Outcome: | The proposed corpus spans four genres of multi-party conversations from different modalities. |
Spatial AMR: Expanded Spatial Annotation in the Context of a Grounded Minecraft Corpus (2020.lrec-1)
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| Challenge: | Existing annotation tools for spatial relations capture fine-grained semantics and pragmatics derived from spatial information. |
| Approach: | They propose an extension to the Abstract Meaning Representation annotation schema that captures fine-grained spatial information in grounded corpora. |
| Outcome: | The proposed tool can handle fine-grained spatial relationships grounded in quantized space. |
Mind the Gap between the Application Track and the Real World (2023.acl-short)
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| Challenge: | Recent advances in NLP have led to a rise in inter-disciplinary and application-oriented research. |
| Approach: | They examine the relationship between motivations described in NLP papers and models and evaluations which comprise the proposed solution. |
| Outcome: | The proposed solution improves educational dialog understanding system when used in a realistic classroom environment. |
Structured Tuning for Semantic Role Labeling (2020.acl-main)
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| Challenge: | Recent neural network-driven semantic role labeling systems have shown impressive improvements in F1 scores. |
| Approach: | They propose a framework to tune models using softened constraints only at training time. |
| Outcome: | The proposed framework outperforms the baseline model with minimal training time and consistent improvements under low-resource scenarios. |
Building a Broad Infrastructure for Uniform Meaning Representations (2024.lrec-main)
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Julia Bonn, Matthew J. Buchholz, Jayeol Chun, Andrew Cowell, William Croft, Lukas Denk, Sijia Ge, Jan Hajič, Kenneth Lai, James H. Martin, Skatje Myers, Alexis Palmer, Martha Palmer, Claire Benet Post, James Pustejovsky, Kristine Stenzel, Haibo Sun, Zdeňka Urešová, Rosa Vallejos, Jens E. L. Van Gysel, Meagan Vigus, Nianwen Xue, Jin Zhao
| Challenge: | This paper reports the first release of the UMR data set for six languages . it includes annotations for six different languages that vary greatly in terms of their linguistic properties and resource availability. |
| Approach: | They report the first release of the UMR data set for six languages . they describe on-going efforts to enlarge the data set and extend it to other languages - including Navajo, Navájo, and Sanapaná . |
| Outcome: | The first release of the UMR data set includes annotations for six languages . the language dataset is available for free and can be extended to other languages if needed . |
X-AMR Annotation Tool (2024.eacl-demo)
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| Challenge: | X-AMR annotation tool is designed for annotating key corpus-level event semantics. |
| Approach: | They propose a new annotation tool for annotation of key corpus-level event semantics using machine assistance. |
| Outcome: | The proposed tool enhances the user experience and improves annotation efficiency. |
Linear Cross-document Event Coreference Resolution with X-AMR (2024.lrec-main)
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Shafiuddin Rehan Ahmed, George Arthur Baker, Evi Judge, Michael Reagan, Kristin Wright-Bettner, Martha Palmer, James H. Martin
| Challenge: | Event Coreference Resolution (ECR) is expensive both for automated systems and manual annotations. |
| Approach: | They propose a graphical representation of events anchored around individual mentions using a cross-document version of Abstract Meaning Representation. |
| Outcome: | The proposed model is anchored around individual mentions using a cross-document version of Abstract Meaning Representation. |
NewsClaims: A New Benchmark for Claim Detection from News with Attribute Knowledge (2022.emnlp-main)
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Revanth Gangi Reddy, Sai Chetan Chinthakindi, Zhenhailong Wang, Yi Fung, Kathryn Conger, Ahmed ELsayed, Martha Palmer, Preslav Nakov, Eduard Hovy, Kevin Small, Heng Ji
| Challenge: | Current claims detection methods focus on sentence analysis, ignoring other attributes . a key element of identifying misinformation is detecting the claims and the arguments that have been presented. |
| Approach: | They propose a benchmark for attribute-aware claim detection in the news domain . they extend the problem to include extraction of additional attributes related to each claim . |
| Outcome: | The proposed system performs well on the test, but human performance is still poor. |
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. |
Human-in-the-loop Schema Induction (2023.acl-demo)
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Tianyi Zhang, Isaac Tham, Zhaoyi Hou, Jiaxuan Ren, Leon Zhou, Hainiu Xu, Li Zhang, Lara Martin, Rotem Dror, Sha Li, Heng Ji, Martha Palmer, Susan Windisch Brown, Reece Suchocki, Chris Callison-Burch
| Challenge: | Existing approaches to event-centric natural language understanding (NLU) have been limited to linear and temporal ones. |
| Approach: | They propose a human-in-the-loop schema induction system powered by GPT-3 . they show that it transfers to new domains more easily than previous approaches . |
| Outcome: | The proposed system transfers to new domains more easily than previous approaches and reduces human curation. |
Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation (2021.acl-long)
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| Challenge: | Compared with general natural language texts, sentences from scientific papers usually possess wider contexts between knowledge elements. |
| Approach: | They propose a novel biomedical Information Extraction model to extract scientific entities and events from English research papers using Abstract Meaning Representation (AMR) they construct a sentence-level knowledge graph from an external knowledge base and encode it to improve the model's understanding of complex scientific concepts. |
| Outcome: | The proposed model can extract scientific entities and events from scientific literature and improve its understanding of complex scientific concepts. |
Leveraging Active Learning to Minimise SRL Annotation Across Corpora (2023.starsem-1)
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| Challenge: | In this paper, we investigate the application of active learning to semantic role labeling (SRL) using Bayesian Active Learning by Disagreement (BALD). |
| Approach: | They propose a sentence-focused selection method that is based off of previous methods of using model dropout to approximate a Gaussian process for SRL. |
| Outcome: | The proposed selection method improves on three different domain corpora on three domains with a large and diverse corpus. |
Cross-document coreference: An approach to capturing coreference without context (D19-62)
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| Challenge: | a cross-document coreference annotation schema was developed to extract timelines in the clinical domain. |
| Approach: | They propose a cross-document coreference annotation schema that is governed by schematic rules to create meaningful and consistent cross- document relations. |
| Outcome: | The proposed approach produces an agreement score of 93.77% for identical relations between the two sets of notes. |
From Spatial Relations to Spatial Configurations (2020.lrec-1)
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| Challenge: | Existing spatial representations are not sufficient for describing complex spatial configurations. |
| Approach: | They propose to integrate existing spatial representation languages with an annotation schema to extend the capabilities of existing ones. |
| Outcome: | The proposed language can represent a large set of spatial concepts crucial for reasoning . it integrates with the Abstract Meaning Representation (AMR) annotation schema and annotates text from diverse datasets . |
AMR Beyond the Sentence: the Multi-sentence AMR corpus (C18-1)
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| Challenge: | Abstract Meaning Representation (AMR) is limited to capturing the semantics of individual sentences. |
| Approach: | They propose a corpus that annotates coreference and similar phenomena on top of existing AMRs. |
| Outcome: | The proposed corpus is compared with existing corpora on sentence-level semantics . it shows that it can be used for information extraction and question answering . |
CRAPES:Cross-modal Annotation Projection for Visual Semantic Role Labeling (2023.starsem-1)
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| Challenge: | Existing approaches to image comprehension limit the image to a single action, while text-based approaches label all actions in a sentence. |
| Approach: | They propose to expand GSR to follow more liberal text-based approach to action and participant identification. |
| Outcome: | The proposed approach improves image comprehension on a SWiG dataset by 28.6 points. |
RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System (2021.naacl-demos)
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Haoyang Wen, Ying Lin, Tuan Lai, Xiaoman Pan, Sha Li, Xudong Lin, Ben Zhou, Manling Li, Haoyu Wang, Hongming Zhang, Xiaodong Yu, Alexander Dong, Zhenhailong Wang, Yi Fung, Piyush Mishra, Qing Lyu, Dídac Surís, Brian Chen, Susan Windisch Brown, Martha Palmer, Chris Callison-Burch, Carl Vondrick, Jiawei Han, Dan Roth, Shih-Fu Chang, Heng Ji
| Challenge: | We present a new information extraction system that can construct temporal event graphs from news documents. |
| Approach: | They propose a temporal event graph extraction system that can extract news documents . they extend the system from sentence-level event extraction to cross-document cross-media event extraction . |
| Outcome: | The proposed system can extract temporal event graphs from news documents in multiple languages and multiple data modalities. |
RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios (2022.naacl-demo)
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Xinya Du, Zixuan Zhang, Sha Li, Pengfei Yu, Hongwei Wang, Tuan Lai, Xudong Lin, Ziqi Wang, Iris Liu, Ben Zhou, Haoyang Wen, Manling Li, Darryl Hannan, Jie Lei, Hyounghun Kim, Rotem Dror, Haoyu Wang, Michael Regan, Qi Zeng, Qing Lyu, Charles Yu, Carl Edwards, Xiaomeng Jin, Yizhu Jiao, Ghazaleh Kazeminejad, Zhenhailong Wang, Chris Callison-Burch, Mohit Bansal, Carl Vondrick, Jiawei Han, Dan Roth, Shih-Fu Chang, Martha Palmer, Heng Ji
| Challenge: | Existing methods for event prediction are incomplete and noisy. |
| Approach: | They propose to use news-related event schemas to extract newsworthy events . they build a demo website and include a video demonstrating the framework . |
| Outcome: | The proposed framework can be applied to a wide variety of newsworthy scenarios. |
PropBank Comes of Age—Larger, Smarter, and more Diverse (2022.starsem-1)
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Sameer Pradhan, Julia Bonn, Skatje Myers, Kathryn Conger, Tim O’gorman, James Gung, Kristin Wright-bettner, Martha Palmer
| Challenge: | The PropBank has been used for semantic role labeling for over 20 years . it includes non-verbal predicates, adjectives, prepositions and multi-word expressions . |
| Approach: | They describe the evolution of the PropBank approach to semantic role labeling over the last 20 years . they describe the substantial effort that has gone into ensuring consistency and reliability of the various annotated datasets and resources . |
| Outcome: | The PropBank has been used for more than 20 years to test semantic role labeling systems. |
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation (2021.naacl-demos)
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Qingyun Wang, Manling Li, Xuan Wang, Nikolaus Parulian, Guangxing Han, Jiawei Ma, Jingxuan Tu, Ying Lin, Ranran Haoran Zhang, Weili Liu, Aabhas Chauhan, Yingjun Guan, Bangzheng Li, Ruisong Li, Xiangchen Song, Yi Fung, Heng Ji, Jiawei Han, Shih-Fu Chang, James Pustejovsky, Jasmine Rah, David Liem, Ahmed ELsayed, Martha Palmer, Clare Voss, Cynthia Schneider, Boyan Onyshkevych
| Challenge: | a new framework to digest relevant biomedical knowledge is needed to combat COVID-19 . quantity of research results is a bottleneck, and false information promoted in publications . |
| Approach: | a team of researchers has developed a framework to extract multimedia knowledge elements from scientific literature to combat COVID-19. |
| Outcome: | a new framework extracts fine-grained multimedia knowledge elements from scientific literature . it provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence . the framework is based on a case study of drug repurposing . |
Meaning Representations for Natural Languages: Design, Models and Applications (2022.emnlp-tutorials)
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| Challenge: | This tutorial reviews the design of common meaning representations and SoTA models for predicting meaning representation models. |
| Approach: | This tutorial reviews the design of common meaning representations and SoTA models for predicting meaning representation models. |
| Outcome: | This tutorial reviews the design of common meaning representations and SoTA models for predicting meaning representation models . it also reviews the applications of meaning representation in downstream NLP tasks and real-world applications . |
Learning Semantic Role Labeling from Compatible Label Sequences (2023.findings-emnlp)
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| Challenge: | Prior work has shown that cross-task interaction helps, but only explored multitask learning so far. |
| Approach: | They propose a framework that jointly models VerbNet and PropBank labels as one sequence and enforcing Semlink constraints during decoding improves the overall F1 . |
| Outcome: | The proposed model outperforms the prior best in-domain model by 3.5 (VerbNet) and 0.8 (PropBank). |
RESIN-EDITOR: A Schema-guided Hierarchical Event Graph Visualizer and Editor (2023.emnlp-demo)
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Khanh Duy Nguyen, Zixuan Zhang, Reece Suchocki, Sha Li, Martha Palmer, Susan Windisch Brown, Jiawei Han, Heng Ji
| Challenge: | Existing IE tools for atomic events are limited when applied to such complex events. |
| Approach: | They propose to use event schemas to guide the organization of complex events and to edit hierarchical graphs. |
| Outcome: | The proposed tool outperforms existing IE visualization tools in both IE result analysis and general model improvements. |
Event Semantic Knowledge in Procedural Text Understanding (2023.starsem-1)
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| Challenge: | Annotators’ reliance on commonsense knowledge to annotate implicit state information is a challenge for entity state tracking. |
| Approach: | They propose a method for entity state tracking that incorporates commonsense entity-centric knowledge from ConceptNet into a BERT-based neural-symbolic architecture. |
| Outcome: | The proposed model outperforms existing models on the ProPara dataset and is domain-agnostic. |
Automatically Extracting Qualia Relations for the Rich Event Ontology (C18-1)
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| Challenge: | a new study uses qualia relations extracted from the Suggested Upper Merged Ontology to extract information about entities . human annotators find qualia relationships and origins of the information to be reasonable . |
| Approach: | They propose to extract qualia from the Generative Lexicon to extract quealia . they assume the theoretical framework of the Generative Lexicons . |
| Outcome: | The proposed method extracts information from the Suggested Upper Merged Ontology (SUMO) human annotators find the extracted information to be reasonable, the authors show . |
GLAMR: Augmenting AMR with GL-VerbNet Event Structure (2024.lrec-main)
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Jingxuan Tu, Timothy Obiso, Bingyang Ye, Kyeongmin Rim, Keer Xu, Liulu Yue, Susan Windisch Brown, Martha Palmer, James Pustejovsky
| Challenge: | Abstract Meaning Representation (AMR) is a general-purpose semantic encoding for language. |
| Approach: | They propose an AMR interpretation of Generative Lexicon semantic components using a verb-net-encoded verb-node graph. |
| Outcome: | The proposed extension is compatible with current AMR specification and can be automated. |
ReCAP: Semantic Role Enhanced Caption Generation (2024.lrec-main)
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| Challenge: | Current vision language models lack specificity and overlook various aspects of the image. |
| Approach: | They propose to use semantic roles as control signals to guide captions to specific argument structures by focusing on specific objects and their associated semantic roles instead of general descriptions. |
| Outcome: | The proposed framework produces captions that exhibit enhanced quality, diversity, and controllability. |
Integrating Generative Lexicon Event Structures into VerbNet (L18-1)
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| Challenge: | Efforts to use the verb lexicon's semantic representations have revealed a need to revise the form to allow for greater flexibility in representing complex events. |
| Approach: | They propose to restrict the form to first-order representations to simplify use by planners and integrate with the Generative Lexicon's event structure. |
| Outcome: | The proposed representations simplify use by and integration with planners and allow for greater flexibility in representing complex events and for a more nuanced portrayal of the Agent's role. |
Abstract Meaning Representation of Constructions: The More We Include, the Better the Representation (L18-1)
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Claire Bonial, Bianca Badarau, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Tim O’Gorman, Martha Palmer, Nathan Schneider
| Challenge: | Abstract Meaning Representation (AMR) uses a flexible pattern or template of multiple lexical items to provide semantic representation of certain constructions. |
| Approach: | They propose to expand the AMR project's lexicon of predicate senses to include entries for a growing set of constructions. |
| Outcome: | The proposed approach provides coverage for the annotation of certain types of constructions. |
The New Propbank: Aligning Propbank with AMR through POS Unification (L18-1)
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| Challenge: | Existing Propbank corpus converts sense labels to a format which is more compatible with AMR and more robust to sparsity. |
| Approach: | They propose a corpus which converts existing Propbank sense labels to a new unified format which is more compatible with AMR and more robust to sparsity. |
| Outcome: | The proposed format is more compatible with AMR and robust to sparsity. |
The Russian PropBank (2020.lrec-1)
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| Challenge: | Using proposition bank for Russian, we can automatically project semantic role labels from English to Russian. |
| Approach: | They propose a proposition bank for Russian that automatically projects semantic role labels from English to Russian. |
| Outcome: | The proposed resource automatically projectes semantic role labels from English to Russian. |
CAMRA: Copilot for AMR Annotation (2023.emnlp-demo)
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| Challenge: | Abstract Meaning Representation (AMR) is a formalism for deep lexical semantic representation. |
| Approach: | They introduce a web-based tool for constructing AMR from natural language text . CAMRA incorporates AMR parser models as coding co-pilots . |
| Outcome: | The proposed tool is based on the prototyping of existing AMR editors and integrates Propbank roleset lookup as an autocomplete feature. |