| FrameNet | |
|---|---|
| Mission statement | Building a lexical database based on a theory of meaning calledframe semantics. |
| Commercial? | No (freely available for download) |
| Type of project | Lexical database (containing: frames, frame elements(FE), lexical units (LU), examples sentences, and frame relations) |
| Location | International Computer Science Institute inBerkeley, California |
| Owner | Collin Baker (current project manager) |
| Founder | Charles J. Fillmore |
| Established | 1997; 29 years ago (1997) |
| Website | framenet |
FrameNet is a group of onlinelexical databases based upon the theory of meaning known asFrame semantics, developed by linguistCharles J. Fillmore. The project's fundamental notion is simple: most words' meanings may be best understood in terms of a semantic frame, which is a description of a certain kind of event, connection, or item and its actors.
As an illustration, the act of cooking usually requires the following: a cook, the food being cooked, a container to hold the food while it is being cooked, and a heating instrument.[1] Within FrameNet, this act is represented by a frame namedApply_heat, and its components (Cook,Food,Container, andHeating_instrument), are referred to as frame elements (FEs). TheApply_heat frame also lists a number of words that represent it, known as lexical units (LUs), likefry,bake,boil, andbroil.
Other frames are simpler. For example,Placing only has anagent or cause, atheme—something that is placed—and the location where it is placed. Some frames are more complex, likeRevenge, which contains more FEs (offender, injury, injured party, avenger, and punishment).[citation needed] As in the examples ofApply_heat andRevenge below, FrameNet's role is to define the frames and annotate sentences to demonstrate how the FEs fit syntactically around the word that elicits the frame.[1]
A frame is a schematic representation of a situation involving various participants, props, and other conceptual roles. Examples of frame names areBeing_born andLocative_relation. A frame in FrameNet contains a textual description of what it represents (a frame definition), associated frame elements, lexical units, example sentences, and frame-to-frame relations.
Frame elements (FE) provide additional information to the semantic structure of a sentence. Each frame has a number of core and non-core FEs which can be thought of as semantic roles. Core FEs are essential to the meaning of the frame while non-core FEs are generally descriptive (such as time, place, manner, etc.)[2] For example:
FrameNet includes shallow data on syntactic roles that frame elements play in the example sentences. For example, for a sentence like "She was born about AD 460", FrameNet would markShe as anoun phrase referring to theChild frame element, and "about AD 460" as anoun phrase corresponding to theTime frame element. Details of how frame elements can be realized in a sentence are important because this reveals important information about thesubcategorization frames as well as possiblediathesis alternations (e.g. "John broke the window" vs. "The window broke") of a verb.
Lexical units (LUs) are lemmas, with their part of speech, that evoke a specific frame. In other words, when an LU is identified in a sentence, that specific LU can be associated with its specific frame(s). For each frame, there may be many LUs associated to that frame, and also there may be many frames that share a specific LU; this is typically the case with LUs that have multiple word senses.[2] Alongside the frame, each lexical unit is associated with specific frame elements by means of the annotated example sentences.
For example, lexical units that evoke theComplaining frame (or more specific perspectivized versions of it, to be precise), include the verbscomplain,grouse,lament, and others.[5]
Frames are associated with example sentences and frame elements are marked within the sentences. Thus, the sentence
is associated with the frameBeing_born, whileShe is marked as the frame elementChild and "about AD 460" is marked asTime.[3]
From the start, the FrameNet project has been committed to looking at evidence from actual language use as found in text collections like theBritish National Corpus. Based on such example sentences, automaticsemantic role labeling tools are able to determine frames and mark frame elements in new sentences.
FrameNet also exposes statistics on thevalence of each frame; that is, the number and position of the frame elements within example sentences. The sentence
falls in the valence pattern
which occurs twice in the FrameNet's annotation report for theborn.v lexical unit,[3] namely:
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FrameNet additionally captures relationships between different frames using relations. These include the following:
FrameNet has proven to be useful in a number of computational applications, because computers need additional knowledge in order to recognize that "John sold a car to Mary" and "Mary bought a car from John" describe essentially the same situation, despite using two quite different verbs, different prepositions and a different word order. FrameNet has been used in applications likequestion answering,paraphrasing, recognizingtextual entailment, andinformation extraction, either directly or by means ofSemantic Role Labeling tools. The first automatic system forSemantic Role Labeling (SRL, sometimes also referred to as "shallow semantic parsing") was developed by Daniel Gildea andDaniel Jurafsky based on FrameNet in 2002.[6] Semantic Role Labeling has since become one of the standard tasks in natural language processing, with the latest version (1.7) of FrameNet now fully supported in theNatural Language Toolkit.[7]
Since frames are essentially semantic descriptions, they are similar across languages, and several projects have arisen over the years that have relied on the original FrameNet as the basis for additional non-English FrameNets, for Spanish, Japanese, German, and Polish, among others.