Comments (3)
The short answer is that ParZu uses CYK parsing internally, and the main reason it (mostly) remains fast for long sentences is aggressive pruning of hypotheses.
It seems that in this case, the list of links is interpreted as a huge noun phrase (lines 70-140), which explodes the search space.
I updated parzu_server.py to catch pexpect timeouts, and there's now also an option to increase the timeout. If you want, you can also fiddle with the parameters 'levels', 'aggressive_start' and 'alter' in core/ParZu_parameters.py to do more aggressive pruning.
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Thanks ... the text that gets passed on to ParZu is pretty rubbish, in other cases, there are artefacts of bad conversion from HTML or similar. From my point of view, I could just try to recognise some of the most frequent oddities (like URLs, HTML entities etc) and replace them with some token that will get ignored by Parzu (what would be good for this?).
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It looks like the HTML wasn't the main problem, but the long sequence of names and similar in the second half. My recommendation would be that if you extract something that was originally a list, to treat each item in the list as a separate sentence. Not sure if you're able to change your HTML conversion this way.
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Related Issues (20)
- Executing "create_statistics.sh" HOT 3
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