71–80 of 80 posts
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The autotldr bot on reddit gets a lot of praise: http://smmry.com (demo here) https://np.reddit.com/r/autotldr/comments/31bfht/theory_auto...
Worth mentioning here, the text summarization engines are pretty much only usable on news articles or text with clean paragraph structure (yes, non-tech literature works too). Popular text summarization tools as they stand now, fails on anything else.
> Do I enjoy participating in the act of piloting an aircraft? Or am I expressing an appreciation for man-made vehicles engaged in movement through the air on wings
Clearly the latter, as the former begets the infinitive, "I love to fly ...".
Maybe I am wrong, going by the American usage of the gerund I clearly am, but then "I want going flying" sounds ridiculous in any case. Maybe I am missing the difference, so as a second language speaker, I'd love to be corrected.
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That's exactly the issue. The way we learn them is through world experience, which is sometimes hard to figure out how to transfer into a computer. Example: "I dropped the egg on my glass living room table and it broke!" "I dropped my hammer on my glass living room table and it broke!" These are both ill-defined semantically, but if you asked most native English speakers "what broke" for each sentence, they'd probabl…
context is everything. "A violent mob requested a demonstration from the councilmen. The councilmen refused the permit, because they feared the violence." I suspect, grammar begets normalization, with primary and secondary keys just like in relational databases. People are just not very good at it. EG. I'd contest the consistency of those 1000 grammar rules . Point in case, the word "violence" needs the definite arti…
No, searching for "inciting violence"/"fearing violence" in Google gives thousands of hits. (Also in Google Books, if you want to claim all these websites are wrong.)
It is perfectly OK to use "violence" without an article.
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I'm not sure what methods they use, but the "single sentence reply suggestions" created by Google's Inbox are the highest quality natural language generation that I have come across.
I believe this is the paper that describes the approach they are using: http://www.kdd.org/kdd2016/papers/files/Paper_1069.pdf Looks less like NLG, and more like picking existing responses from a (probably huge) corpus using ML. Hard to replicate unless you have access to the kind of data Google has.
> Take this simple example: “I love flying planes.” > Do I enjoy participating in the act of piloting an aircraft? Or am I expressing an appreciation for man-made vehicles engaged in movement through the air on wings Clearly the latter, as the former begets the infinitive, "I love to fly ...". Maybe I am wrong, going by the American usage of the gerund I clearly am, but then "I want going flying" sounds ridiculous in…
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context is everything. "A violent mob requested a demonstration from the councilmen. The councilmen refused the permit, because they feared the violence." I suspect, grammar begets normalization, with primary and secondary keys just like in relational databases. People are just not very good at it. EG. I'd contest the consistency of those 1000 grammar rules . Point in case, the word "violence" needs the definite arti…
> Point in case, the word "violence" needs the definite article, because violence is an abstract concept (which the parent missed). No, searching for "inciting violence"/"fearing violence" in Google gives thousands of hits. (Also in Google Books, if you want to claim all these websites are wrong.) It is perfectly OK to use "violence" without an article.
Wouldn't omitting the the in my sentence mean, they feared violence in general? Sure, broad contracts are welcome, but then there couldn't be a specific answer to who they are. I guess that's in agreement with what you said.
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I believe this is the paper that describes the approach they are using: http://www.kdd.org/kdd2016/papers/files/Paper_1069.pdf Looks less like NLG, and more like picking existing responses from a (probably huge) corpus using ML. Hard to replicate unless you have access to the kind of data Google has.
If you think about it, all natural language generation is simply picking from a list of possible words to go next. They just do that at a sentence level.
> Why is NLP Hard? ... Language is highly ambiguous - it relies on subtle cues and contexts to convey meaning. This is true, but it is only part of the answer. Another part of the answer is what I call the Long Tail of Grammar. It turns out that if you try to write down all the rules of grammar, you will not get 40 or 60 rules, but something more like 100s or maybe even 1000s of rules. Most of those rules are obscure…
> compare the phrase "peeled peach" with "hairy-peeled peach" Is that a rule of grammar, or simply the meanings of the adjectives "peeled" and "hairy-peeled"?
- Xed Y = a Y that has been Xed, where X is a verb
- Xed Y = a Y that is equipped with an X, where X is a noun.
For the latter pattern, consider examples such as "red-lipped woman", "rosy-fingered dawn", "sharp-toothed pike", "horned owl", etc.
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Not just that, grammar rules can come into existence/change spontaneously. Here's an example and name for this phenomenon: Because syntactic change.
That isn't really a rule change. The lexicon just added a new preposition, 'because,' to the old list. It means almost the same thing as the old preposition 'because of.' There's a difference between coining a new word and changing a grammar rule.
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The autotldr bot on reddit gets a lot of praise: http://smmry.com (demo here) https://np.reddit.com/r/autotldr/comments/31bfht/theory_auto...
Worth mentioning here, the text summarization engines are pretty much only usable on news articles or text with clean paragraph structure (yes, non-tech literature works too). Popular text summarization tools as they stand now, fails on anything else.