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Comment by andrewstuart2 | Hacker News Reader

One of my favorite examples that I heard in a David Rock talk which I can no longer find on youtube: "Time flies like an arrow":

Time moves swiftly and in one direction.

Record the speed of flies in the same way you would an arrow.

Time flies, which are a kind of fly, are fond of an arrow. (e.g. Time flies like an arrow, fruit flies like a banana).

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It sounds like you're talking about garden-path sentences [0], and in particular: "time flies like an arrow; fruit flies like a banana" [1]. These are sentences whose structure tricks the reader into making an incorrect parse. My favourite of these has always been: "The horse raced past the barn fell".

[0] https://en.wikipedia.org/wiki/Garden-path_sentence

[1] https://en.wikipedia.org/wiki/Time_flies_like_an_arrow;_frui...

I've always enjoyed the multiple valid parses of "Time flies like an arrow". I can't wait for AI to generate more Escher sentences like "More people have been to Russia than I have" ( https://en.m.wikipedia.org/wiki/Comparative_illusion )

You know, I only just now got the second interpretation of that sentence. I always thought of it like "Time flies like an arrow (straight and in one direction), Fruit flies like a banana (when thrown)"

Obvious in hindsight...

Same here, except it's comparing fly's flight trajectory to that of a banana is new to me.

"The horse raced past the barn fell, which has been haunted since all those teenagers were murdered there."

(Noun-adjective is a rare formation, but amusingly more common in the same situations where the author uses rare and archaic definitions like the adjective "fell".)

"I eat my rice with butter." could mean that you use butter as a utensil to eat your rice with. There is often an unlikely way of parsing the sentence that gives an alternate meaning. The point is to test the computer to see if it can distinguish the likely parse from an unlikely one.

These aren't really alternate _parses_ though (in the sense that they don't give different parse trees). They do highlight the different possible meanings of "with" though.

I think "I eat my rice with chicken" vs "I eat my rice with children" vs "I eat my rice with chopsticks" is the canonical example here.

There's a whole field in NLP involved in showing what changes happen to entities mentioned in a sentence as a a side effect of the sentence, and this example shows it pretty well.

Wouldnt those be different parse trees? Like the "with X" could either be attached either to the verb or the noun

I think it's more clear if you say "I usually eat X with Y", i.e. Y it's either the company, the tool or the condiment that you eat with (contrasted with "I'm eating my X", where X is a dish like "rice with chicken")

Yes, possibly.

A good demonstration that context (and cultural conditioning) is everything to understand what a text actually means.

Not to mention something that almost all NLP systems are resounding terrible at - short-term memory. If we've been talking about corporate financials for an hour and I say 'Justify the margins', it should be crystal clear what I mean. But most automated systems try to operate without a hint of memory or 'state' being tracked.

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