Capturing syntactico-semantic regularities among terms: An application of the FrameNet methodology to terminology (original) (raw)
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Putting FrameNet data into the ISO linguistic annotation framework
Proceedings of the ACL 2003 workshop on Linguistic annotation getting the model right -, 2003
This paper describes FrameNet , an online lexical resource for English based on the principles of frame semantics , and considers the FrameNet database in reference to the proposed ISO model for linguistic annotation of language resources (ISO TC37 SC4 ) . We provide a data category specification for frame semantics and FrameNet annotations in an RDF-based language. More specifically, we provide a DAML+OIL markup for lexical units, defined as a relation between a lemma and a semantic frame, and frame-to-frame relations, namely Inheritance and Subframes. The paper includes simple examples of FrameNet annotated sentences in an XML/RDF format that references the project-specific data category specification.
Conference: International FrameNet Workshop 2020. Towards a Global, Multilingual FrameNet. Proceedings, Workshop of the Language Resources and Evaluation, LREC, 2020
The methodology developed within the FrameNet project is being used to compile resources in an increasing number of specialized fields of knowledge. The methodology along with the theoretical principles on which it is based, i.e. Frame Semantics, are especially appealing as they allow domain-specific resources to account for the conceptual background of specialized knowledge and to explain the linguistic properties of terms against this background. This paper presents a methodology for building a multilingual resource that accounts for terms of the environment. After listing some lexical and conceptual differences that need to be managed in such a resource, we explain how the FrameNet methodology is adapted for describing terms in different languages. We first applied our methodology to French and then extended it to English. Extensions to Spanish, Portuguese and Chinese were made more recently. Up to now, we have defined 190 frames: 112 frames are new; 38 are used as such; and 40 are slightly different (a different number of obligatory participants; a significant alternation, etc.) when compared to Berkeley FrameNet.
Lexicography. Journal of Asialex, 2018
This paper argues for an approach to terms – based on Frame Semantics (Fillmore 1976; Fillmore and Baker 2010) – that takes into account their linguistic properties and shows how terms and their properties are connected formally to the expression of knowledge in specialized fields. I briefly present the theoretical assumptions underlying this proposal. The main part of the article describes the methodology devised to implement the proposal in two terminological resources that are under development at the Observatoire de linguistique Sens-Texte (OLST). The methodology that comprises seven main steps is based on that of FrameNet (FrameNet 2017; Ruppenhofer et al. 2016), the lexical implementation of Frame Semantics. I illustrate the methodology by applying it to terms that belong to the field of endangered species, a subfield of the environment.
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Proceedings of the Third Linguistic Annotation Workshop on - ACL-IJCNLP '09, 2009
WordNet and FrameNet are widely used lexical resources, but they are very different from each other and are often used in completely different ways in NLP. In a case study in which a short passage is annotated in both frameworks, we show how the synsets and definitions of WordNet and the syntagmatic information from FrameNet can complement each other, forming a more complete representation of the lexical semantic of a text than either could alone. Close comparisons between them also suggest ways in which they can be brought into alignment.
A Bilingual Electronic Dictionary for Frame Semantics
2000
Frame semantics is a linguistic theory which is currently gaining ground. The creation of lexical entries for a large number of words presupposes the development of complex lexical acquisition techniques in order to identify the vocabulary for describing the elements of a 'frame'. In this paper, we show how a lexical-semantic database compiled on the basis of a bilingual (English-French) dictionary can be used to identify some general frame elements which are relevant in a frame-semantic approach such as the one adopted in the FrameNet project (Fillmore & Atkins 1998, Gahl 1998). The database has been systematically enriched with explicit lexical-semantic relations holding between some elements of the microstructure of the dictionary entries. The manifold relationships have been labelled in terms of lexical functions, based on Mel'cuk's notion of co-occurrence and lexical-semantic relations in Meaning-Text Theory (Mel'cuk et al. 1984). We show how these lexical f...
Using language technology resources and tools to construct Swedish FrameNet
Having access to large lexical and grammatical resources when creating a new language resource is essential for its enhancement and enrichment. This paper describes the interplay and interactive utilization of different language technology tools and resources, in particular the Swedish lexicon SALDO and Swedish Constructicon, in the creation of Swedish FrameNet. We show how integrating resources in a larger infrastructure is much more than the sum of the parts. 1 Introduction This paper describes how Swedish language technology resources are exploited to construct Swedish FrameNet (SweFN), 1 a lexical-semantic resource that has been expanded from and constructed in line with Berkeley FrameNet (BFN). The resource has been developed within the framework of the theory of Frame Semantics (Fillmore, 1985). According to this theory, semantic frames including their participants represent cognitive scenarios as schematic representations of events, objects, situations, or states of affairs. The participants are called frame elements (FEs) and are described in terms of semantic roles such as AGENT, LOCATION, or MANNER. Frames are evoked by lexical units (LUs) which are pairings of lemmas and meanings. To get a visualization of the notion of semantic frames consider the frame Vehicle landing. It has the following definition in BFN: "A flying VEHICLE comes to the ground at a GOAL in a controlled fashion, typically (but not necessarily) operated by an operator." VEHICLE and GOAL are the core elements that together with the description uniquely characterize the frame. Their semantic types are Physical object and Location. The non-core elements of the frame are: CIRCUMSTANCES, COTHEME, DEGREE, DEPICTIVE, EVENT DESCRIPTION, FREQUENCY, GOAL CONDITIONS, MANNER, MEANS, MODE OF TRANSPORTATION, PATH, PERIOD OF ITERATIONS, PLACE, PURPOSE, RE ENCODING, SOURCE, and TIME. The lexical units evoking the frame are: land.v, set down.v, and touch down.v. In addition, the frame contains a number of example sentences which are annotated in terms of LUs and FEs. These sentences carry valence information about different syntactic realizations of the FEs and about their semantic characteristics. Currently SweFN contains around 1,150 frames with over 29,000 lexical units of which 5,000 are verbs, and also 8,300 semantically and syntactically annotated sentences, selected from a corpus. SweFN has mainly been created manually, but as a response to an ever increasing complexity, volume, and specialization of textual evidence, the creation of SweFN is enhanced with automated Natural Language Processing (NLP) techniques. In contrast to the construction of English resources, as well as the construction of framenets for other languages, the resources used to construct SweFN are all linked in a unique infrastructure of language resources. 2 The development of framenets in other languages FrameNet-like resources have been developed in several languages and have been exploited in a range of NLP applications such as semantic parsing (Das et al., 2014), information extraction (Moschitti et This work is licenced under a Creative Commons Attribution 4.0 International License.
Proceedings of the Third Workshop on Computational Typology and Multilingual NLP
FrameNet and the Multilingual FrameNet project have produced multilingual semantic annotations of parallel texts that yield extremely fine-grained typological insights. Moreover, frame semantic annotation of a wide cross-section of languages can provide information on the limits of Frame Semantics (Fillmore, 1982, 1985). Multilingual semantic annotation offers critical input for research on linguistic diversity and recurrent patterns in computational typology. Drawing on results from FrameNet annotation of parallel texts, this paper proposes frame semantic annotation as a new component to complement the state of the art in computational semantic typology. 1
This paper is a sequel of my paper for the Maastricht Session of the 2010 Duo Colloquium. There I discussed a (cognitive-) linguistic system that may be used by students of translation and starting translators as a discovery procedure for meaning determination in terminology and translation, viz. the Lexical-System-like Structure as I defined it in the framework of TCM (for Two-Cycle Model of Grammar) (Alinei, Thelen). I compared it with Componential Analysis and argued that it can do more than the latter. The background for the Maastricht paper was my experience that when translators do not find the support they need for rendering as precisely as possible in language and culture (B) (i.e. the target text) a message that is formulated in language and culture (A) (i.e. the source text), and for dealing adequately with terminology, they end up having to rely on themselves. Generally, the resources available to them range from various types of dictionary (printed as well as digital editions), term banks, text books, to the internet, machine translation tools, CAT tools, localisation tools, translation memories to personal contacts. These resources may cover domain-specific information, general information as well as linguistic information. The experience and maturity of the student of translation tends to determine which types of resource he may decide to use, in what situations and how often. He may use these resources in order to confirm or check ideas about/suggestions for translation and terminology solutions, in order to look for and find such solutions, and in order to prove the correctness or plausibility of solutions decided on. In this paper, I will discuss a number of other linguistic models, viz. WordNet (e.g. Fellbaum, Miller), and frames (e.g. Fillmore) and compare them with Lexical-System-like Structures on the point of their ability to provide practical help for translators.
Frame Semantics across Languages: Towards a Multilingual FrameNet
2018
FrameNet is a lexical resource that provides rich semantic representations of the core English vocabulary based on Fillmore’s Frame Semantics, with more than 200k manually annotated examples. Resources based on FrameNet have now been created for roughly a dozen languages. This workshop will present current research on aligning Frame Semantic resources across languages and automatic frame semantic parsing in English and other languages. We will explore the extent to which semantic frames are similar across languages and the implications for theories of semantic universals, the practice of translation (whether human or machine), and multilingual knowledge representation. Does not require prior familiarity with Frame Semantics. 1 Description The FrameNet Project at the International Computer Science Institute (ICSI, http://framenet. icsi.berkeley.edu) has created a detailed lexical database of contemporary English, (currently more than 13,000 lexical units in 1,200 semantic frames) bas...