FrameNet

FrameNet is a three-year NSF-supported project in corpus-based computational lexicog- raphy, now in its second year (NSF IRI-9618838, "Tools for Lexicon Building"). The project's key features are (a) a commitment …...

The development of FrameNet, a large database of semantically annotated sen- tences, has primed research into statistical methods for semantic tagging. We ad- vance previous work by adopting a Maximum …...

This paper reports on experiments in clas- sifying the semantic role annotations as- signed to prepositional phrases in both the PENN TREEBANK and FRAMENET. In both cases, experiments are done …...

In this paper we have designed and experi- mented novel convolution kernels for automatic classification of predicate arguments. Their main property is the ability to process struc- tured representations. Support …...

We present a novel automatic approach to constructing a bilingual semantic network—the BiFrameNet, to enhance statistical and transfer-based machine translation systems. BiFrameNet is a frame semantic representation, and contains semantic …...

As part of its description of lexico-semantic predicate frames or conceptual structures, the FrameNet project defines a set of semantic roles specific to the core predicate of a sentence. Recently, …...

This paper presents SemFrame, a system that induces frame semantic verb classes from WordNet and LDOCE. Semantic frames are thought to have significant potential in resolving the paraphrase problem challenging …...

This paper investigates whether human as- sociations to verbs as collected in a web experiment can help us to identify salient verb features for semantic verb classes. Assuming that the …...

This article describes a robust seman- tic parser that uses a broad knowledge base created by interconnecting three ma- jor resources: FrameNet, VerbNet and PropBank. The FrameNet corpus con- tains …...

We describe our contribution to the SemEval task on Frame-Semantic Structure Extrac- tion. Unlike most previous systems de- scribed in literature, ours is based on depen- dency syntax. We also …...

Shallow semantic parsing, the automatic identification and labeling of sentential con- stituents, has recently received much atten- tion. Our work examines whether seman- tic role information is beneficial to question …...

Almost all automatic semantic role label- ing (SRL) systems rely on a preliminary parsing step that derives a syntactic struc- ture from the sentence being analyzed. This makes the choice …...

In this paper, we introduce our Recognizing Textual Entailment (RTE) system developed on the basis of Lexical Entailment between two text excerpts, namely the hypothesis and the text. To extract …...

This paper presents a novel automatic approach to partially integrate FrameNet and WordNet. In that way we expect to extend FrameNet coverage, to en- rich WordNet with frame semantic information …...

AbstractIn this paper we present a new FrameNet-based Shallow Semantic Parser. Shallow Semantic Parsing has been a popular Natural Language Processing task since the 2004 and 2005 CoNLL Shared Task …...

AbstractThis paper presents a corpus of annotated motion events and their event structure. We consider motion events triggered by a set of motion evoking words and contemplate both literal and …...

AbstractThis paper presents an algorithm for aligning FrameNet lexical units to WordNet synsets. Both, FrameNet and WordNet, are well-known as well as widely-used resources by the entire research community. They …...

AbstractThis paper focuses on the improvement of the conceptual structure of FrameNet (FN) for the sake of applying this resource to knowledge-intensive NLP tasks requiring reasoning, such as question answering, …...

AbstractThis paper presents a novel automatic approach to partially integrate FrameNet and WordNet. In that way we expect to extend FrameNet coverage, to enrich WordNet with frame semantic information and …...

AbstractLexical resources are basic components of many text processing system devoted to information extraction, question answering or dialogue. In paste years many resources have been developed such as FrameNet and …...

AbstractSemantic Role Labeling cannot be performed without an associated linguistic resource. A key resource for such a task is the FrameNet resource based on Fillmore’s theory of frame semantics. Like …...

AbstractDespite the large variety of corpora in the biomedical domain their annotations differ in many respects, e.g., the coverage of different, highly specialized knowledge domains, varying degrees of granularity of …...

. This paper presents and analyzes the KOLON System, created to facilitate Ko- rean Natural Language Processing (KNLP) and to improve experimental results through the KOLON Ontology. It is currently …...

AbstractThis work presents a method of linking verbs and their valency frames in VerbaLex database developed at the Centre for NLP at the Faculty of Informatics Masaryk University to the …...

We present a novel method for FrameNet- based semantic role labeling (SRL), fo- cusing on limitations posed by the limited coverage of available annotated data. Our SRL model is based …...

Text-to-scene conversion requires knowledge about how actions and locations are expressed in language and realized in the world. To provide this knowlege, we are creating a lexical resource (VigNet) that …...

AbstractWe analyze how different conceptions of lexical semantics affect sense annotations and how multiple sense inventories can be compared empirically, based on annotated text. Our study focuses on the MASC …...

Widely accepted resources for semantic parsing, such as PropBank and FrameNet, are not perfect as a semantic role label- ing framework. Their semantic roles are not strictly defined; therefore, their …...

Semantic role classification accuracy for most languages other than English is constrained by the small amount of annotated data. In this pa- per, we demonstrate how the frame-to-frame relations described …...

We present UBY, a large-scale lexical- semantic resource combining a wide range of information from expert-constructed and collaboratively constructed resources for English and German. It currently contains nine resources in …...

AbstractThis paper proposes a method for discovering semantic frames (Fillmore, 1982, 1985; Fillmore et al., 2003) in specialized domains. It is assumed that frames are especially relevant for capturing the …...

In this paper, we present work on ex- tracting social networks from unstructured text. We introduce novel features de- rived from semantic annotations based on FrameNet. We also introduce novel …...

AbstractThis paper presents the Predicate Matrix v1.1, a new lexical resource resulting from the integration of multiple sources of predicate information including FrameNet, VerbNet, PropBank and WordNet. We start from …...

. According to Frame Semantics (Fillmore 1976), words’ meaning are best understood considering the semantic frame they play a role in, for the frame is what gives them context. FrameNet …...

We present a multilingual corpus of Wikipedia and Twitter texts annotated with FRAMENET 1.5 semantic frames in nine different languages, as well as a novel technique for weakly supervised cross-lingual …...

Recent work has successfully leveraged the semantic information extracted from lexi- cal knowledge bases such as WordNet and FrameNet to improve English event corefer- ence resolvers. The lack of comparable …...

AbstractThis paper presents the Predicate Matrix 1.3, a lexical resource resulting from the integration of multiple sources of predicate information including FrameNet, VerbNet, PropBank and WordNet. This new version of …...

AbstractFrame semantics is a theory of linguistic meanings, and is considered to be a useful framework for shallow semantic analysis of natural language. FrameNet, which is based on frame semantics, …...

AbstractWe present a VerbNet-based annotation scheme for semantic roles that we explore in an annotation study on German language data that combines word sense and semantic role annotation. We reannotate …...

AbstractWe present a new approach for generating role-labeled training data using Linked Lexical Resources, i.e., integrated lexical resources that combine several resources (e.g., Word-Net, FrameNet, Wiktionary) by linking them on …...

AbstractThis paper proposes a new method for Italian verb classification -and a preliminary example of resulting classes- inspired by Levin (1993) and VerbNet (Kipper-Schuler, 2005), yet partially independent from these …...

Frames defined in FrameNet (FN) share highly similar structures with events in ACE event extraction program. An even- t in ACE is composed of an event trig- ger and a …...

AbstractRecent research shows the importance of linking linguistic knowledge resources for the creation of large-scale linguistic data. We describe our approach for combining two English resources, FrameNet and sar-graphs, and …...

AbstractWe introduce a new method for frame-semantic parsing that significantly improves the prior state of the art. Our model leverages the advantages of a deep bidirectional LSTM network which predicts …...

AbstractCreating annotated frame lexicons such as PropBank and FrameNet is expensive and labor intensive. We present a method to induce an embedded frame lexicon in an minimally supervised fashion using …...

AbstractFrame-semantic parsing and semantic role labelling, that aim to automatically assign semantic roles to arguments of verbs in a sentence, have become an active strand of research in NLP. However, …...

Metaphors are not only remarkably pervasive in both informal and formal text, but reflect fundamental properties of human cognition. This paper presents an algorithmic model that suggests metaphoric means of …...

AbstractThis paper describes CzEngClass, a bilingual lexical resource being built to investigate verbal synonymy in bilingual context and to relate semantic roles common to one synonym class to verb arguments …...

Noun compounds are interesting constructs in Natural Language Processing (NLP). Interpretation of noun compounds is the task of uncovering a relationship between component nouns of a noun compound. There has …...

AbstractThis paper presents Unsupervised Lexical Frame Induction, Task 2 of the International Workshop on Semantic Evaluation in 2019. Given a set of prespecified syntactic forms in context, the task requires …...

AbstractThis paper outlines procedures for enhancing WordNet with conceptual information from FrameNet. The mapping of the two resources is non-trivial. We define a number of techniques for the validation of …...

AbstractRecent work has attempted to enhance vector space representations using information from structured semantic resources. This process, dubbed retrofitting (Faruqui et al., 2015), has yielded improvements in word similarity performance. …...

AbstractAlthough FrameNet is recognized as one of the most fine-grained lexical databases, its coverage of lexical units is still limited. To tackle this issue, we propose a two-step frame induction …...

AbstractIn this paper we describe and evaluate syntactic and semantic aspects of Arbobanko, a treebank for the artificial language Esperanto, as well as tools and methods used in the production …...

AbstractFrameNet is a lexical semantic resource based on the linguistic theory of frame semantics. A number of framenet development strategies have been reported previously and all of them involve exploration …...

Given a noun compound (NC), we address the problem of predicting the appropriate semantic label linking the constituents of the NC. This problem is called Noun Compound Interpretation (NCI). We …...

AbstractHumans create things for a reason. Ancient people created spears for hunting, knives for cutting meat, pots for preparing food, etc. The prototypical function of a physical artifact is a …...

AbstractResearch into representation learning models of lexical semantics usually utilizes some form of intrinsic evaluation to ensure that the learned representations reflect human semantic judgments. Lexical semantic similarity estimation is …...

Contextualized word representations have proven useful for various natural language pro- cessing tasks. However, it remains unclear to what extent these representations can cover hand-coded semantic information such as se- …...

AbstractFrame semantic parsing is a fundamental NLP task, which consists of three subtasks: frame identification, argument identification and role classification. Most previous studies tend to neglect relations between different subtasks …...

AbstractThis paper begins with the premise that adverbs are neglected in computational linguistics. This view derives from two analyses: a literature review and a novel adverb dataset to probe a …...

AbstractIn this paper, we propose FrameBERT, a BERT-based model that can explicitly learn and incorporate FrameNet Embeddings for concept-level metaphor detection. FrameBERT not only achieves better or comparable performance to …...

AbstractRecent works in Event Argument Extraction (EAE) have focused on improving model generalizability to cater to new events and domains. However, standard benchmarking datasets like ACE and ERE cover less …...

AbstractRecent studies have demonstrated the usefulness of contextualized word embeddings in unsupervised semantic frame induction. However, they have also revealed that generic contextualized embeddings are not always consistent with human …...