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From Grant Ingersoll <>
Subject Re: Lucene for a linguistic corpus
Date Tue, 08 Jan 2013 17:49:28 GMT
Hi Igor,

On Jan 5, 2013, at 7:36 AM, Igor Shalyminov wrote:

> Hello!
> I'm considering Lucene as an engine for linguistic corpus search.
> There's a feature in this search: each word is treated as ambiguuos - i.e., it has got
multiple sets of grammatical annotations (there's a fixed maximum of these sets number - a
word can have at most 8 parses).
> For an example, in the phrase "A man saw a elephant" "saw" has annotations as follows
(we also say that its position in index is 1234):
> {lemma: see, pos: verb, tense: past}, {lemma: saw, pos: noun, number: singular}
> Normally, we index each annotation as an independent feature (i.e., there will be posting
lists for "lemma", "pos", "number", etc.). And the problem is, for the query "pos = Verb AND
number = Singular" we DON'T want to find the position 1234 because they appeared in different
> As a solution one may consider indexing all annotation subsets (this would increase index
size and queries complicatedness), searching for regexps (but the search will be dead slow)

Might be worth trying, esp. in Lucene 4 with some of the new automaton stuff.  At least you
will have a baseline.

> , or indexing parses, not words (but queries with given distance between words will break
up) - these solutions are not acceptable.
> I think, it would be more effective to insert parse index in each attribute's posting
list entry as a payload and use it at the intersectiion stage. E.g., we have a posting list
for 'pos = Verb' like ...|...|1.1234|...|..., and a posting list for 'number = Singular':
...|...|2.1234|...|... While processing a query like 'pos = Verb AND number = singular' at
all stages of posting list processing 'x.1234' will be accepted until the intersection stage
at which they will be rejected because of non-corresponding parse indexes.
> I am also new to Lucene, so could you please tell me if this idea is implementable in
Lucene, and how much effort does the implementation take?

You might be able to insert your parses as payloads on a term and then implement a scorer
extension (override computePayloadFactor) to handle your join cases for a given word.  You
may also need to extend PayloadQuery or PayloadTermQuery.  Note, I don't know how well this
will perform.

So, "saw" would have the two lemmas above and then your logic for the new Query class would
be able to distinguish, via the two payloads that neither satisfies the Verb, singular option
and would then return a score of 0.  There is likely other work involved to make sure it all
works appropriately, but that is where I would start.  Others might have different approaches.

I'd have to play around w/ the code a bit more to make this work, but I think it is doable
in Lucene.  I can't say how long it would take you, b/c I have no clue as to what you know
about Lucene.  For someone who knows Lucene, it's probably anywhere from a few days to a week
or two.  

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