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 parses.
>
> 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.
-Grant
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