Search Results for author:
Found 95 papers, 14 papers with code
AutoAspect: Automatic Annotation of Tense and Aspect for Uniform Meaning Representations
The annotation tool combines syntactic and semantic cues to assign aspects on a sentence-by-sentence basis, following a sequence of rules that each output a UMR aspect.
Tuning Deep Active Learning for Semantic Role Labeling
Active learning has been shown to reduce annotation requirements for numerous natural language processing tasks, including semantic role labeling (SRL).
Predicate Representations and Polysemy in VerbNet Semantic Parsing
Despite recent advances in semantic role labeling propelled by pre-trained text encoders like BERT, performance lags behind when applied to predicates observed infrequently during training or to sentences in new domains.
TopGuNN: Fast NLP Training Data Augmentation using Large Corpora
Acquiring training data for natural language processing systems can be expensive and time-consuming.
Automatic Entity State Annotation using the VerbNet Semantic Parser
Tracking entity states is a natural language processing task assumed to require human annotation.
Aligning Images and Text with Semantic Role Labels for Fine-Grained Cross-Modal Understanding
As vision processing and natural language processing continue to advance, there is increasing interest in multimodal applications, such as image retrieval, caption generation, and human-robot interaction.
SemLink 2.0: Chasing Lexical Resources
The SemLink resource provides mappings between a variety of lexical semantic ontologies, each with their strengths and weaknesses.
PropBank Comes of Age—Larger, Smarter, and more Diverse
This paper describes the evolution of the PropBank approach to semantic role labeling over the last two decades.
Defining and Learning Refined Temporal Relations in the Clinical Narrative
We present refinements over existing temporal relation annotations in the Electronic Medical Record clinical narrative.
RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios
We introduce RESIN-11, a new schema-guided event extraction&prediction framework that can be applied to a large variety of newsworthy scenarios.
Speech Is Not Enough: Interpreting Nonverbal Indicators of Common Knowledge and Engagement
Our goal is to develop an AI Partner that can provide support for group problem solving and social dynamics.
SCI 3.0: A Web-based Schema Curation Interface for Graphical Event Representations
To understand the complexity of global events, one must navigate a web of interwoven sub-events, identifying those most impactful elements within the larger, abstract macro-event framework at play.
Adapting Abstract Meaning Representation Parsing to the Clinical Narrative -- the SPRING THYME parser
This paper is dedicated to the design and evaluation of the first AMR parser tailored for clinical notes.
Linear Cross-document Event Coreference Resolution with X-AMR
We then linearize the ECR with a novel multi-hop coreference algorithm over the event graphs.
X-AMR Annotation Tool
This paper presents a novel Cross-document Abstract Meaning Representation (X-AMR) annotation tool designed for annotating key corpus-level event semantics.
RESIN-EDITOR: A Schema-guided Hierarchical Event Graph Visualizer and Editor
In this paper, we present RESIN-EDITOR, an interactive event graph visualizer and editor designed for analyzing complex events.
CAMRA: Copilot for AMR Annotation
In this paper, we introduce CAMRA (Copilot for AMR Annotatations), a cutting-edge web-based tool designed for constructing Abstract Meaning Representation (AMR) from natural language text.
Learning Semantic Role Labeling from Compatible Label Sequences
In this paper, we eliminate such issue with a framework that jointly models VerbNet and PropBank labels as one sequence.
GLEN: General-Purpose Event Detection for Thousands of Types
Finally, we perform error analysis and show that label noise is still the largest challenge for improving performance for this new dataset.
Dependency Dialogue Acts -- Annotation Scheme and Case Study
DDA combines and adapts features from existing dialogue annotation frameworks, and emphasizes the multi-relational response structure of dialogues in addition to the dialogue acts and rhetorical relations.
Human-in-the-Loop Schema Induction
Schema induction builds a graph representation explaining how events unfold in a scenario.
Human-guided Collaborative Problem Solving: A Natural Language based Framework
We consider the problem of human-machine collaborative problem solving as a planning task coupled with natural language communication.
NewsClaims: A New Benchmark for Claim Detection from News with Attribute Knowledge
In this work, we present NewsClaims, a new benchmark for attribute-aware claim detection in the news domain.
A Graphical Interface for Curating Schemas
Much past work has focused on extracting information like events, entities, and relations from documents.
Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation
In this paper, we propose a novel biomedical Information Extraction (IE) model to tackle these two challenges and extract scientific entities and events from English research papers.
What Would a Teacher Do? Predicting Future Talk Moves
Recent advances in natural language processing (NLP) have the ability to transform how classroom learning takes place.
RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System
We present a new information extraction system that can automatically construct temporal event graphs from a collection of news documents from multiple sources, multiple languages (English and Spanish for our experiment), and multiple data modalities (speech, text, image and video).
From Spatial Relations to Spatial Configurations
To exhibit the applicability of our representation scheme, we annotate text taken from diverse datasets and show how we extend the capabilities of existing spatial representation languages with the fine-grained decomposition of semantics and blend it seamlessly with AMRs of sentences and discourse representations as a whole.
Abstract Meaning Representation
Natural Language Understanding
+1
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions.
Spatial AMR: Expanded Spatial Annotation in the Context of a Grounded Minecraft Corpus
This paper presents an expansion to the Abstract Meaning Representation (AMR) annotation schema that captures fine-grained semantically and pragmatically derived spatial information in grounded corpora.
Leveraging Non-Specialists for Accurate and Time Efficient AMR Annotation
Abstract Meaning Representations (AMRs), a syntax-free representation of phrase semantics are useful for capturing the meaning of a phrase and reflecting the relationship between concepts that are referred to.
The Russian PropBank
This paper presents a proposition bank for Russian (RuPB), a resource for semantic role labeling (SRL).
Structured Tuning for Semantic Role Labeling
We start with a strong baseline (RoBERTa) to validate the impact of our approach, and show that our framework outperforms the baseline by learning to comply with declarative constraints.
Cross-document coreference: An approach to capturing coreference without context
This paper discusses a cross-document coreference annotation schema that was developed to further automatic extraction of timelines in the clinical domain.
Linguistic Analysis Improves Neural Metaphor Detection
In the field of metaphor detection, deep learning systems are the ubiquitous and achieve strong performance on many tasks.
ClearTAC: Verb Tense, Aspect, and Form Classification Using Neural Nets
This paper proposes using a Bidirectional LSTM-CRF model in order to identify the tense and aspect of verbs.
Enhancing biomedical word embeddings by retrofitting to verb clusters
Verbs play a fundamental role in many biomed-ical tasks and applications such as relation and event extraction.
Explaining Simple Natural Language Inference
The vast amount of research introducing new corpora and techniques for semi-automatically annotating corpora shows the important role that datasets play in today{'}s research, especially in the machine learning community.
VerbNet Representations: Subevent Semantics for Transfer Verbs
This paper announces the release of a new version of the English lexical resource VerbNet with substantially revised semantic representations designed to facilitate computer planning and reasoning based on human language.
Automatically Extracting Qualia Relations for the Rich Event Ontology
Commonsense, real-world knowledge about the events that entities or {``}things in the world{''} are typically involved in, as well as part-whole relationships, is valuable for allowing computational systems to draw everyday inferences about the world.
Developing and Evaluating Annotation Procedures for Twitter Data during Hazard Events
As social media grows more popular, an increasing number of people are using social media platforms to obtain and share information about approaching threats and discuss their interpretations of the threat and their protective decisions.
AMR Beyond the Sentence: the Multi-sentence AMR corpus
There are few corpora that endeavor to represent the semantic content of entire documents.
Improving Classification of Twitter Behavior During Hurricane Events
We show that feature-based and deep learning methods provide different benefits for tweet classification, and ensemble-based methods using linguistic, temporal, and geospatial features can effectively classify user behavior.
Leveraging Syntactic Constructions for Metaphor Identification
Identification of metaphoric language in text is critical for generating effective semantic representations for natural language understanding.
SemEval 2018 Task 6: Parsing Time Normalizations
This paper presents the outcomes of the Parsing Time Normalization shared task held within SemEval-2018.
SemEval-2017 Task 12: Clinical TempEval
Clinical TempEval 2017 aimed to answer the question: how well do systems trained on annotated timelines for one medical condition (colon cancer) perform in predicting timelines on another medical condition (brain cancer)?
Towards Problem Solving Agents that Communicate and Learn
Agents that communicate back and forth with humans to help them execute non-linguistic tasks are a long sought goal of AI.
The Rich Event Ontology
In this paper we describe a new lexical semantic resource, The Rich Event On-tology, which provides an independent conceptual backbone to unify existing semantic role labeling (SRL) schemas and augment them with event-to-event causal and temporal relations.
Unsupervised AMR-Dependency Parse Alignment
In this paper, we introduce an Abstract Meaning Representation (AMR) to Dependency Parse aligner.
Linguistic features for Hindi light verb construction identification
To build our system, we carry out a linguistic analysis of Hindi LVCs using Hindi Treebank annotations and propose two new features that are aimed at capturing the diversity of Hindi LVCs in the corpus.
A corpus of preposition supersenses in English web reviews
We present the first corpus annotated with preposition supersenses, unlexicalized categories for semantic functions that can be marked by English prepositions (Schneider et al., 2015).
A Proposition Bank of Urdu
The present size of this Propbank is around 180, 000 tokens which is double-propbanked by the two annotators for simple predicates.
Large Multi-lingual, Multi-level and Multi-genre Annotation Corpus
High accuracy for automated translation and information retrieval calls for linguistic annotations at various language levels.
Comprehensive and Consistent PropBank Light Verb Annotation
Recent efforts have focused on expanding the annotation coverage of PropBank from verb relations to adjective and noun relations, as well as light verb constructions (e. g., make an offer, take a bath).
Focusing Annotation for Semantic Role Labeling
We show that the least probable sentences provide dramatic improved system performance over the baseline, especially when only a small portion of the data is annotated.
Single Classifier Approach for Verb Sense Disambiguation based on Generalized Features
In order to overcome this problem, we create a single classifier to be applied to rare or unseen verbs in a new text.
Criteria for Identifying and Annotating Caused Motion Constructions in Corpus Data
While natural language processing performance has been improved through the recognition that there is a relationship between the semantics of the verb and the syntactic context in which the verb is realized, sentences where the verb does not conform to the expected syntax-semantic patterning behavior remain problematic.
Mapping CPA Patterns onto OntoNotes Senses
In this paper we present an alignment experiment between patterns of verb use discovered by Corpus Pattern Analysis (CPA; Hanks 2004, 2008, 2012) and verb senses in OntoNotes (ON; Hovy et al. 2006, Weischedel et al. 2011).
Not an Interlingua, But Close: Comparison of English AMRs to Chinese and Czech
Abstract Meaning Representations (AMRs) are rooted, directional and labeled graphs that abstract away from morpho-syntactic idiosyncrasies such as word category (verbs and nouns), word order, and function words (determiners, some prepositions).
PropBank: Semantics of New Predicate Types
This research focuses on expanding PropBank, a corpus annotated with predicate argument structures, with new predicate types; namely, noun, adjective and complex predicates, such as Light Verb Constructions.
Temporal Annotation in the Clinical Domain
The corpus is available to the community and has been proposed for use in a SemEval 2015 task.
Empty Argument Insertion in the Hindi PropBank
This paper examines both linguistic behavior and practical implication of empty argument insertion in the Hindi PropBank.
Foundations of a Multilayer Annotation Framework for Twitter Communications During Crisis Events
In times of mass emergency, vast amounts of data are generated via computer-mediated communication (CMC) that are difficult to manually collect and organize into a coherent picture.
