>> 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}
>>
>> 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.
We're working on something very similar.
Are there really posting lists like this (e.g., separate lists for pos=Verb,
number=Singular) for things in Payloads? I think some previous discussion
was saying this kind of posting list is not available. I couldn't find
anything like that in the documentation about the index format. If there
are, this would be really efficient.
> 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.
We've done it this way before, storing a slightly different set of
information in the Payload. I thought making use of a Payload, though,
requires you to iterate through all the tokens, whether in the Analyzer
(i.e., in a TokenFilter) or Similarity (in an overridden scorePayload()
function).
If I'm right, then filtering this out at intersection time might not be
quite as efficient as you're talking about, but it's definitely a reasonable
way to do it.
stephen
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