FrameNet
FrameNet is a group of online lexical databases based upon the theory of meaning known as Frame semantics, developed by linguist Charles 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. Within FrameNet, this act is represented by a frame named, and its components, are referred to as frame elements. The frame also lists a number of words that represent it, known as lexical units, like fry, bake, boil, and broil.
Other frames are simpler. For example, only has an agent or cause, a theme—something that is placed—and the location where it is placed. Some frames are more complex, like, which contains more FEs. As in the examples of and 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.
Concepts
Frames
A frame is a schematic representation of a situation involving various participants, props, and other conceptual roles. Examples of frame names are and. A frame in FrameNet contains a textual description of what it represents, associated frame elements, lexical units, example sentences, and frame-to-frame relations.Frame elements
Frame elements 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 For example:- The only core FE of the frame is called ; non-core FEs,,, etc.
- Core FEs of the frame include the,, and, while non-core FEs include a,, etc.
Lexical units
Lexical units 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. 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. 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 the frame, include the verbs complain, grouse, lament, and others.
Example sentences
Frames are associated with example sentences and frame elements are marked within the sentences. Thus, the sentenceis associated with the frame, while She is marked as the frame element and "about AD 460" is marked as.
From the start, the FrameNet project has been committed to looking at evidence from actual language use as found in text collections like the British National Corpus. Based on such example sentences, automatic semantic role labeling tools are able to determine frames and mark frame elements in new sentences.
Valences
FrameNet also exposes statistics on the valence of each frame; that is, the number and position of the frame elements within example sentences. The sentencefalls in the valence pattern
which occurs twice in the FrameNet's annotation report for the lexical unit, namely:
Frame relations
FrameNet additionally captures relationships between different frames using relations. These include the following:Inheritance: When one frame is a more specific version of another, more abstract, parent frame. Anything that is true about the parent frame must also be true about the child frame, and a mapping is specified between the frame elements of the parent and the frame elements of the child.Perspectivization: A neutral frame is connected to a frame with a specific perspective of the same scenario. For example, is considered from the perspective of the buyer in and from that of the seller in.Subframe: Some frames refer to complex scenarios that consist of several individual states or events that can be described by separate frames. For example, is composed of,, and so on.Precedence: This relation captures the temporal order that holds between subframes of a complex frame. For example, within the frame, the subframe is preceded by the subframe.Causative and Inchoative: These two relations mark, for causative- and inchoative-aspect frames, the separate stative frame they refer to. For example, the stative is described by the causative and by the inchoative frame.Using: This relation marks a frame that in some way involves another frame. For example, uses both and, but does not inherit from either of them because there is no clear correspondence of frame elements.See also: Connects frames that bear some resemblance but need to be distinguished carefully.Applications
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 like question answering, paraphrasing, recognizing textual entailment, and information extraction, either directly or by means of Semantic Role Labeling tools. The first automatic system for Semantic Role Labeling was developed by Daniel Gildea and Daniel Jurafsky based on FrameNet in 2002. Semantic Role Labeling has since become one of the standard tasks in natural language processing, with the latest version of FrameNet now fully supported in the Natural Language Toolkit.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.