Difference in dependency parsing

[aoldoni]

Sentence "A two-tier scheme (Pang and Lee, 2004) where sentences are first classified as subjective versus objective , and then applying the sentiment classifier on only the subjective sentences further improves performance." gives different tree locally than in displacy.

[aoldoni]

Logged issue in Spacy Github https://github.com/spacy-io/spaCy/issues/480

[DBWangWei]

Hi Alisson,

I am away on a trip and will return on 5 Oct. So for this week, I cannot fix my schedule till Tue. In the worst case, let's communicate by email.

Wei On 25 Sep 2016 16:35, "Alisson Oldoni" notifications@github.com wrote:

Logged issue in Spacy Github spacy-io/spaCy#480 https://github.com/spacy-io/spaCy/issues/480

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[aoldoni]

One thing we could attempt here is for maybe for Dr. @DBWangUNSW to please attempt parsing a sentence locally and see if yours is the same as displacy, then we can narrow to be a issue with my local computer.

E.g.: this sentence: "A two-tier scheme (Pang and Lee, 2004) where sentences are first classified as subjective versus objective , and then applying the sentiment classifier on only the subjective sentences further improves performance."

Thanks.

[aoldoni]

Related with https://github.com/aoldoni/comp9596/issues/21 since moving to "Stanford" e.g.: could entirely avoiding this problem, while being slower.

[aoldoni]

After some investigation, it is quite challenging to add the stanford parse properly in python, but it is something I can continue to work on.

[aoldoni]

Other sentence parsed incorrectly:

• "As remarked earlier, an automated reasoning facility effectively reduces manual effort and improves match quality and efficiency."
• "A two-tier scheme (Pang and Lee, 2004) where sentences are first classified as subjective versus objective , and then applying the sentiment classifier on only the subjective sentences further improves performance."
• "Consequently, IPL improves read performance by reducing the number of log pages to read from flash memory when recreating a logical page because log pages do not increase indefinitely (i.e., is bound) due to merging."
• "It has been shown that using logic-oriented categorical features not only significantly improves the efficiency of sequences matching but also achieves high accuracy in contentbased retrieval of human-motion data."
• "A subsequent work is PWJoin [7] that improves the performance of PJoin utilizing both the window semantics and punctuation semantics."
• "A two-tier scheme (Pang and Lee, 2004) where sentences are first classified as subjective versus objective , and then applying the sentiment classifier on only the subjective sentences further improves performance."
• "(2008) report that just filtering the phrase table by the socalled well-formed target dependency structure does not help, yet adding a target dependency language model improves performance significantly."