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It says 'train line' right in that sentence. Where is the ambiguity? That's the thing -- in your (wetware) mind it says "train line." But the sentence itself

It says 'train line' right in that sentence. Where is the ambiguity? That's the thing -- in your (wetware) mind it says "train line." But the sentence itself it just says "line", which can mean a whole much of things.

dominotw 10y ago
But the sentence itself it just says "line", which can mean a whole much of things. Ok i changed the sentence to include 'train lines' CTA buses were moving, but slowly, and ‘L’ train lines were operating, but with delays. Blue, Brown, Orange, Green and Red Lines were running normally. Even this is no good CTA buses were moving, but slowly, and ‘L’ train lines were operating, but with delays. Green train line was operating normally. didn't make any difference. Were you able to get it to parse correctly somehow?
- kafkaesq 10y ago
  Now we have a different problem -- in that the new examples aren't idiomatic. There's no reason we should expect it to identify the phrases 'L' train line and 'L' line with equal accuracy, because the former is something basically nobody says -- while the latter is something everyone (even someone unfamiliar with that particular city) understands. But hey -- I'm not defending the API's accuracy ;)
nostrademons 10y ago
It does say "'L' trains" in the previous sentence and "trains" in the following sentence. And from bduerst's post, it appears that GCNLP does use non-local information to determine an interpretation. So in theory, there should be enough information within the paragraph to identify these. The tricky part is that I don't really see a way that a computer could disambiguate between "train line" and "bus line" given the information in that paragraph; the only way that you could do this is to have knowledge of Chicago's transit system. (Indeed, as a human, I didn't know for sure that it was talking about a train line rather than some other mass transit system until Googling.)

dominotw 10y ago

But the sentence itself it just says "line", which can mean a whole much of things. Ok i changed the sentence to include 'train lines' CTA buses were moving, but slowly, and ‘L’ train lines were operating, but with delays. Blue, Brown, Orange, Green and Red Lines were running normally. Even this is no good CTA buses were moving, but slowly, and ‘L’ train lines were operating, but with delays. Green train line was operating normally. didn't make any difference. Were you able to get it to parse correctly somehow?

kafkaesq 10y ago
Now we have a different problem -- in that the new examples aren't idiomatic. There's no reason we should expect it to identify the phrases 'L' train line and 'L' line with equal accuracy, because the former is something basically nobody says -- while the latter is something everyone (even someone unfamiliar with that particular city) understands. But hey -- I'm not defending the API's accuracy ;)

nostrademons 10y ago

It does say "'L' trains" in the previous sentence and "trains" in the following sentence. And from bduerst's post, it appears that GCNLP does use non-local information to determine an interpretation. So in theory, there should be enough information within the paragraph to identify these. The tricky part is that I don't really see a way that a computer could disambiguate between "train line" and "bus line" given the information in that paragraph; the only way that you could do this is to have knowledge of Chicago's transit system. (Indeed, as a human, I didn't know for sure that it was talking about a train line rather than some other mass transit system until Googling.)