![]() He graduated magna cum laude from Cornell and received a law degree cum laude from Georgetown. He graduated cum laude from Fordham, from which he received a law degree, magna cum laude. She graduated magna cum laude from Tulane and has a law degree cum laude from Harvard. He graduated magna cum laude from Columbia and received his law degree cum laude from Harvard. He graduated magna cum laude from Yale and received a law degree cum laude from Harvard. He graduated cum laude from Penn and has a law degree cum laude from Northwestern. The couple met at Princeton, from which she graduated cum laude, he magna cum laude. He graduated cum laude from Princeton, and received a law degree cum laude from Harvard. She graduated cum laude from Princeton and received a law degree, cum laude, from Harvard. They also received law degrees from Duke, he cum laude and she magna cum laude. The couple graduated from Brandeis University, she magna cum laude and he cum laude. " Florida Senator Marco Rubio-the Tea Party darling cum empathic party savior cum presidential candidate cum #NeverTrump Republican cum Trump supporter-issued a statement saying, "I disagree with on many things, but I disagree with his opponent on virtually everything. If you want four tracks worth of scurrying, baroque, mutated, wonky, blissed out, baleful, beatific, grime- cum-R&B- cum-club-music- cum-ambient- cum-whatever-the-fuck-this-is then you're in luck. "The naïf cum babe in the woods cum new guy in town cum man-boy cum…visitor-in-an-unusual-environment conceit was, uh…was very, very good to me," he said.Ĭommerzbank acknowledged it had been trading in cum cum situations. Length: All <=10 words 10-20 words 20-30 words 30-50 words So for internal fake cum work, there are lubes augmented to look more like cum, like Cum Lube and Spunk. Structure: All Simple Compound Complex Compound-Complex So I think the purely weighted approach, as used in the original random sentence generator, is the only way to get random sentences meant for humans.Type: All Declarative Interrogative Exclamative In fact, I'd say we want some sentences like tu de'u kerfa di ko'a do de ko ti to die in the arse. So from what I've seen, we don't want every sentence to have an equal chance. Now it generates boring sentences which at least have LE in them, like la pilji ku ralju gigdo le'i co'e melbi ku. No amount of weighting would fix the fact that 1 word is easier to fit in a random sentence than 3, so it was always anaphora everywhere. In contrast, since this generator seems to never drop KU, every sentence which has a LE in it has to also have a KU in it. jay) And there are LOTS of 9-word sentences with 8 anaphora and a bridi, especially as my weighting steered the sentences away from strange grammatical structures which there could also be lots of. (right, that was the whole point. :) sadly it didn't turn out quite so well. This algorithm gives every 9-word sentence an equal chance of being produced. Sometimes there would be a nai instead of one anaphora, or a two-word tanru for the bridi, but always generally the same thing.Īnd now I see why. The result: nearly every sentence consisted of 8 anaphora filling the places of one bridi. I also repeated things I thought were important, such as sumti, 5 times. Basically, I took options which went directly to another rule without extra stuff, and repeated those 3 times. I took a copy of grammar.300, as you suggested, and modified it. Maybe it's trying to produce the name of its creator? -pne I have noticed that it really likes jai, though. Wonderful! But it looks like it needs some tuning: it gave me jai jai jai na'e jai je'a klesi jai cupra. I don't think I saw the word le anywhere on the page I got. However, I think there still needs to be some sort of weighting - the vast majority of Lojban sentences of length n are ugly things only a computer could love. If anyone would like to take a copy of grammar.300 from the Lojban site and adjust it like that, I'd love to see the result. The only feasible method is to adjust the grammar used to produce sentences by removing rules which produce things you don't want, and duplicating rules for things which you want to have a higher likely hood. So if jbofi'e can parse everything produced by my generator, then that means that jbofi'e is correct.) (My generator produces output using the LLG's official YACC grammar, whereas jbofi'e's grammar is based off of the EBNF grammar. The ones it fails on are visibly malformed. Notably, jbofi'e parses all the validish sentences. Its because I don't fully reverse all of the lexer preprocessing done, yet. Uses an algorithm devised by Bruce McKenzie to ensure that all strings of length n have the same chance of being generated.Ĭurrently not all sentences are valid (a few percent). They're generated from sentence_11 (in the YACC grammar description), so you'll never see fa'o, for instance.
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