Eric Kafe

The present participle of _to stag_ is _stagging_, so the problem is in the morphological processing, and not in the database. Other lemmatizers are available: ``` from nltk.stem import WordNetLemmatizer...

None of the WordNetLemmatizer functions is able to lemmatize _stagging_: ``` from nltk.stem import WordNetLemmatizer as wnl print(wnl().lemmatize("stagging", pos="v")) ``` stagging `print(wnl().morphy("stagging", pos="v"))` None `print(wnl()._morphy("stagging", pos="v"))` [] Here, the solution...

Thanks @pedroborgescruz! If you plan to modify the database, it would be a data issue rather than an nltk issue. Then you should consider submitting your solution to the relevant...

Thanks @ShadokDuBas, your PR yields the following semantics, which seem quite surprising: > S {sleep(the(\x.(cat(x) & belongs(x,the(\x.woman(x))))))} Is this a cat that is also a woman, and belongs to itself?

Yes @arademaker, the cat and the woman should not collapse in the first sentence. But @ShadokDuBas is right in pointing out that this bug is not introduced by this PR,...

@tanin47, could you advise whether _deepcopy_ is needed?

Here is a draft by Gemini 1.5: > This PR aims to address the issue of lexicon modification within the nltk.ccg.chart parser. > However, after careful consideration and discussion, we...

Thanks @ShadokDuBas, I am discovering the ccg module, and don't know much about its implementation yet, but I expect that the truth will emerge through a healthy debate. The quoted...

@ShadokDuBas, after considering [your test](https://github.com/nltk/nltk/issues/3345#issuecomment-2558515950), I agree that instantiations made during parsing leave the lexicon object in a state that is most likely undesirable (maybe unless a user specifically wants...

@stevenbird, which "critical shortcoming of the solution" do you refer to? If it is the example where all the variables are collapsed to "x", it is not caused by this...