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Prosem: Referenzen ergänzt.

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Jim Martens 2014-01-15 13:34:20 +01:00
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prosem/prosempaper.tex
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Now that both methods have been presented with one selected approach each, it is time to discuss them critically. The CYK algorithm solves many problems like ambiguity; at least to a certain degree. But it also is problematic, because of the restriction to CNF. While in theory every context-free grammar can be converted to CNF, in practice it poses ``some non-trivial problems''\cite[p.~475]{Jurafsky2009b}. One of this problems can be explored in conjunction with the second presented method (semantic analysis). ``[T]he conversion to CNF will complicate any syntax-driven approach to semantic analysis''\cite[p.~475]{Jurafsky2009b}. A solution to this problem is some kind of post-processing in which the trees are converted back to the original grammar.\cite{Jurafsky2009b} Another option is to use a more complex dynamic programming algorithm that accepts any kind of context-free grammar. Such an algorithm is the ``Earley Algorithm''\cite[p.~477]{Jurafsky2009b}.
%TODO reference for "easy to compute final meaning representation with given table"
The syntax-driven semantic analysis, as it has been presented, is a powerful method that is easy to understand. But it has one essential problem. It relies upon an existing set of grammar rules with semantic attachments to them. In a real world example such a table would contain thousands of grammar rules.\cite{Russel2010} While it is relatively easy to compute the final meaning representation with such a given table, it is very hard to create the table in the first place. The difficulty to create this table is split into two main issues. The first one being that you must find a grammar specification that fits all your use cases. This problem applies for the syntactic parsing as well. The second issue is that one has to find out the semantic attachments to the grammar rules.
The syntax-driven semantic analysis, as it has been presented, is a powerful method that is easy to understand. But it has one essential problem. It relies upon an existing set of grammar rules with semantic attachments to them. In a real world example such a table would contain thousands of grammar rules. While it is relatively easy to compute the final meaning representation with such a given table, it is very hard to create the table in the first place. The difficulty to create this table is split into two main issues. The first one being that you must find a grammar specification that fits all your use cases. This problem applies for the syntactic parsing as well. The second issue is that one has to find out the semantic attachments to the grammar rules.
This initial workload to create a state, in which the semantic analysis works, is a unique effort.\cite{Jurafsky2009} A restricted environment has a limited set of words and topics compared to an unrestricted environment. An example is a flight check-in automaton that only needs to process a subset of the full English grammar. Therefore this workload is of low importance in such an environment. Even if it takes one month to create such a table by hand or by computing it, the subsequent analysis of input based on this table is rather quick and the initial workload is therefore acceptable. But this is only true for restricted environments. If someone tried to use syntax-driven semantic analysis for the complete language of modern English, the creation of such a table would outweigh any possible usage.
This initial workload to create a state, in which the semantic analysis works, is a unique effort. A restricted environment has a limited set of words and topics compared to an unrestricted environment. An example is a flight check-in automaton that only needs to process a subset of the full English grammar. Therefore this workload is of low importance in such an environment. Even if it takes one month to create such a table by hand or by computing it, the subsequent analysis of input based on this table is rather quick and the initial workload is therefore acceptable. But this is only true for restricted environments. If someone tried to use syntax-driven semantic analysis for the complete language of modern English, the creation of such a table would outweigh any possible usage.
%TODO three options: add reference to claim, introduce necessary knowledge prior to this point or drop it
Comparing the complexity of the two methods it shows a mirror-like image. For the parsing the creation of the grammar is comparatively easy. The presented CYK algorithm works with context-free grammars which are a very restricted set compared to natural languages. But even within these context-free grammars there are ambiguities inside the texts themselves. The creation of the parse trees is therefore more of a problem.