Ling
431/631: Corpus Linguistics
Ben
Bergen
Meeting 9: Framenet
October 15, 2007
Framenet
Corpora are useful
for lexicography – building of lexicons and dictionaries. Framenet is a great
example.
This project
is constructing what could be called the dictionary of the future.
- Gives not just a definition of a word but a
description of the frame
of reference it's embedded in
- Supported by corpus evidence (from the BNC),
with samples linked to the words and frames
From the
Framenet website:
"The aim is to document the range of semantic and syntactic
combinatory possibilities (valences) of each word in each of its senses,
through computer-assisted annotation of example sentences and automatic
tabulation and display of the annotation results."
The lexical
database now has
- about 9,000 lexical units
- in about 600 semantic frames
- linked to about 135,000 annotated sentences.
A frame
is a script-like conceptual structure that describes a particular type of situation,
object, or event and the participants and props involved in it. For instance,
the Travel frame has a Traveler, a Goal, a Source, and perhaps some others.
Language based on this frame includes: commute.v, excursion.n, expedition.n, journey.n, journey.v, junket.n, odyssey.n, peregrination.n, pilgrimage.n, safari.n, tour.n, tour.v, travel.n, travel.v, trip.n, voyage.n, voyage.v
Words
associated with the frame are linked to it. Often, different senses of a polysemous
word (a word with multiple meanings) belongs to different semantic frames. E.g.
commute can also mean to exchange a penalty for a less severe one - this would
be based on another frame (perhaps Substitution, perhaps Punishment, perhaps a
combination of both)
Framenets are
now underway in German, Spanish, and Japanese.
What Framenet
means to you
- Framenet can be useful
- For language
learning/teaching - consider how useful it is not only to have a definition
of a word and some examples, but also statistics on how it's realized
syntactically
- For generating and norming
stimuli - for example if you want to get words belonging to a particular
frame, or make sure that words can appear in certain syntactic
configurations
- For determining the
valence patterns of words, for theoretical reasons or for computational
applications like parsing
- You're not going to be able to build
something the size a Framenet yourself - the English one has taken many
hundreds of thousands (or maybe millions) of person-hours. But if you
think it's useful, you can integrate strategies of Framenet in dictionary
building on a smaller scale.
