Notes on computational linguistics.pdf - UCLA Department of ...

Stabler - Lx 185/209 2003
construction.
(20) With the morphology in or4.pl and the grammar gh4.pl, we can parse:
showParse([’Titus’,laughs]). showParse([’Titus’,will,laugh]).
showParse([’Titus’,eats,a,pie]). showParse([is,’Titus’,laughing]).
showParse([does,’Titus’,laugh]). showParse([what,does,’Titus’,eat]).
(21) Obviously, more complex morphologies (and phonologies) can be represented by FSMs (Ellison, 1994;
Eisner, 1997), but they will all have domains and ranges that are regular languages.
17.3 Better models of the interface
The previous section shows how to translate from input text to written forms of the morphemes, whose syntactic
features are then looked up. We will not develop this idea here, but it is clear that it makes more sense
to translate from the input text directly to the syntactic features. In other words,
represent the lexicon as a finite state machine: input → feature sequences
This would allow us to remove some of the redundancy. In particular, whenever two feature sequences have a
common suffix, that suffix could be shared. However, this model has some other, more serious shortcomings.
17.3.1 Reduplication
In some languages, plurality or other meanings are sometimes expressed not by any particular phonetic string,
but by reduplication, as mentioned earlier on pages 24, 182 above. It is easy to show that the language accepted
by any finite transducer is only a regular language, and hence one that cannot recognize the crossing relations
apparently found in reduplication.
17.3.2 Morphology without morphemes
Reduplication is only one of various kinds of morphemic alterations which do not involve simple affixation
of material with specific phonetic content. Morphemic content can be expressed by word internal changes in
vowel quality, for example, or by prosodic cues. The idea that utterances are sequences of phonetically given
morphemes is not tenable (Anderson, 1992, for example). Rather, a range of morphological processes are
available, and the languages of the world make different selections from them. That means that having just
left and right adjunction as options in head movement is probably inadequate: we should allow various kinds
of expressions of the sequences of elements that we analyze in syntax.
17.3.3 Probabilistic models, and recognizing new words
When we hear new words, we often make assumptions about how they would combine with affixes without
hesitation. This suggests that some kind of similarity metric is at work. The relevant metric is by no means
clear yet, but a wide range of proposals are subsumed by imagining that there is some “edit distance” that
language learners use in identifying related lexical items. The basic idea is this: given some ways of changing
a string (e.g. by adding material to either end of the string, by changing some of the elements of the string, by
copying all or part of the string, etc.), a relation between pairs of strings is given by the number of operations
required to map one to the other. If these operations are weighted, then more and less likely relations can
be specified, and this metric can be adjusted based on what has already been learned (Ristad and Yianilos,
1996). This approach is subsumed by the more general perspective in which the similarity of two sequences
is assessed by the length of the shortest program that can produce one from the other (Chater and Vitányi,
2002).
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