@Ada
What do we do with students/graduates who were fed archaic ideals?
You give them full professorships. ;-)
- Hugh
On Wed, Oct 25, 2023 at 7:29 AM Ada Wan via Corpora corpora@list.elra.info wrote:
Dear Christian, dear all [pls feel free to disregard if not interested]
Discussion on a separate thread is fine.
- Re "whether or not lemmatization is a valid NLP task":
I must first clarify that I am not on this mailing list just for "NLP issues" (however "NLP" should be defined or regardless of whether it should exist as an area with "word"-based or non-general/generalizable methods beyond "machine/computational/automatic processing with (text) data"). Machine processing with data, text/"language" or not, can be done without "words" anyway. I did not just question whether lemmatization is a valid NLP task. I questioned (the necessity/validity of) morphology in general, which would affect the practice of lemmatization.
- Re "lemmas were not invented for NLP":
it depends what "lemmas" and "NLP" refer to. The study of morphology/morphs/morphemes certainly dates back quite some time (e.g. Panini --- in terms of decomposing a "word" into smaller parts). BUT the practice of naming segments as "lemmas" (and not "morphs"/"morphemes") and the use of the term "lemma" might have come from computational linguists/lexicographers and/or computing. Computing practices might have reinforced the practice of lemmatization/segmentation throughout the past decades, since back in the days (e.g. 1960s-1970s? [1]) when memory was more of an issue or when linguistic techniques were leveraged when computing with text.
- Re "Bronze Age dictionaries/word lists of cuneiform languages":
i. some of these are effects of interpretation (much of which dated back to the modern era, e.g. papyrology from the 19th century); ii. I do not argue against the possibility/practice of decomposition in general, but (linguistic) morphology is not a general decomposition approach for its being based on a notion of "stemhood" that can be arbitrary, indeterminate, "culture"/context-specific, and/or idiosyncratic (recall many hard-to-decipher symbols/graphemes on many ancient manuscripts). A more general method would be to decompose in a granularity that is fine enough and recompose based on frequency (as that's also often a pivotal criterion for empirical analyses and interpretations).
- Re "the use of head words in dictionaries is a practice that won't go
away as long as people are going to use dictionaries ... for language learning": many lexical resources (e.g. dictionaries) are based on character n-grams and do not leverage the notion of "head words". The notion of "morphology" is hence orthogonal/irrelevant. (Remark: a few decades ago, it might have been much easier in some parts of the world to get clarity on this --- just by walking into a bookstore or a library and looking at the plethora of lexical resources --- of different types/formats/designs, in general or for particular disciplines. But that practice seems to have (almost) become a lost art now. For "language learning", I'd recommend the immersion method. Nothing beats experiencing communication in multi-dimensional, full-bodied contexts. Use lexical resources only as mnemonics of sorts (don't become too pedantic/addicted on such). Use style guides (or "grammar textbooks") only when pleasing others is necessary. :) Just thought to note to those on this list who might be interested.)
- Re "inflection patterns": please see my reply to Orhan earlier today:
[tweet/x] The solution can be adapted for "(morphological) segmentation" as well. Please let me know if it is fine to you or if you have any objections.
- Re "low resource ... just plain legacy word lists and grammar sketches":
if one works in data collection: for varieties that are still alive, one should record raw and full data when possible and retire the ("colonial") practice of elicitation based on "words". One could also try to obtain parallel data in larger spans instead. For varieties that are extinct, one archives what one has. For what purposes should any "word"-based practices or linguistic morphology be involved?
- "won't go away in corpus linguistics and the philologies":
May it be for corpus linguistics, the philologies, the humanities and the social sciences --- digital or not, for "practical" purposes or not, everything (methods, approaches, interpretations, reception... etc.) can be updated.
- Re "[w]hether or not the use of lemmas ... is a valid task depends on
the use case" and "data modeling": sure, the use of tools can depend on the purpose of the task. But the issue here is: if the use of lemmas is only good for the task of lemmatization, and if the use of lemmatization with text data is only good for linguistic morphology, and when morphology is found not (or no longer) relevant/useful/correct/appropriate, what do we do with a curriculum that overfits on one representation granularity that does not have a solid foundation? What do we do with students/graduates who were fed archaic ideals?
Best Ada (Some often forget that I am also a linguist, not just a "computational person", among other roles/interests.)
[1] My dating references here are supported by: "Algorithms for stemming have been studied in computer science since the 1960s." and "The first published stemmer was written by Julie Beth Lovins in 1968." ( https://en.wikipedia.org/wiki/Stemming) I would've guessed from the 1950s otherwise....
On Wed, Oct 18, 2023 at 9:05 AM Christian Chiarcos via Corpora < corpora@list.elra.info> wrote:
Dear Ada, dear all,
I think it's necessary to discuss this in a separate thread. As for Hugh, he had a practical problem with an existing data set and we can discuss specific solutions for that. As for Ada, whether or not lemmatization is a valid NLP task can be discussed, as well, but this has absolutely nothing to do with the very concrete request for advice on a real problem at hand.
I really don't want to dive into this, but focus on the first part. Of course, there are applications where lemmatization as an NLP task was assumed to be necessary but is no longer needed. But lemmas were not invented for NLP, they were invented for structuring dictionaries and describing morphology actually several millenia before the computer (I'm thinking of Bronze Age dictionaries/word lists of cuneiform languages here, used for teaching Sumerian, but there even in our 3rd m. BCE Sumerian cuneiform corpus from the time when it was still spoken, there was a notion of lemma or head word, and scribes sometimes just wrote that because they were to lazy to write the full morphology). And the use of head words in dictionaries is a practice that won't go away as long as people are going to use dictionaries (be they digital or not) for language learning. And that's equally true for writing textbook grammars and for teaching morphology (you need some kind of base form to describe your inflection patterns), as it is for rule-based morphology (that won't go away, either, even though the use case is more on the low resource side of things ... low resource meaning few corpus data, no parallel data, just plain legacy word lists and grammar sketches). And also, it won't go away in corpus linguistics and the philologies, at least not for use cases where people come from a dictionary perspective.
Whether or not the use of lemmas (note that the question was actually not about lemmatization, but about data modelling) is a valid task depends on the use case. Working with humanists that want that because it's their established practice is a valid use case. We can debate with them, of course, but they are the experts on their use case, and I'd prefer to devote my energy to something more practically relevant, like getting them away from using MS Office for annotations or dictionaries and to use any tool that produces structured output, instead. And already this can be a hard problem that might eventually kill an otherwise interesting project. (Apologies, that's not true of everyone, of course, but those cases exist, and even where people understand the necessity, we still have to work with decades of legacy data to bring into shape.) As for the role of lemmatization in NLP, please continue to discuss without me.
@Ada, you seem to have a very concrete idea in mind how to get humanists away from getting lemmas. I guess that could be an interesting discussion at a conference on DH or language learning -- because this is where the requirement comes from.
Best, Christian
Am Di., 17. Okt. 2023 um 19:45 Uhr schrieb Bilgin, Orhan (Postgraduate Researcher) via Corpora corpora@list.elra.info:
Dear Ada,
I agree that lemmatisation is a construct and is not a universal method for linguistic analyses, but I don't understand why it is imperative that I wean myself from using lemmas.
What is it that restricts my freedom to invent the lemma (a non-universal construct) AĞAÇ-, for example, to refer to the one and only "meaningful thing" that is common to the very many (theoretically infinite, practically probably around 10,000) strings including ağaç, ağacı, ağaca, ağaçlar, ağacımızdaki, ağaçlandırılabilmesinden, ağaçsızlaşmasını, etc. etc.? How (and why) am I supposed to talk about that very large set without using a label for it?
Best,
Orhan Bilgin
On 17 Oct 2023 18:36, Ada Wan via Corpora corpora@list.elra.info wrote:
*This email originated outside the University. Check before clicking links or attachments.* Dear Christian
Re your PS: one doesn't need to debate the use/future of lemmatization, though I'd welcome such as part of scholarship. For those experienced in matters in/of Linguistics, it should be clear that lemmatization was simply a cconstruct, a entry-level philological exercise (esp. for those from Computer Science with less of a background in Linguistics and language(s)). It has been sad that some have picked up the habit of using lemmatization as a heuristic (though for what, specifically?) and might have become, apparently, too addicted to it to let it go. It is imperative that one weans themselves from such habit. Methods for linguistic morphology, e.g. (morphological) parsing or stemming, are not a universal decomposition scheme, nor a universal method for language/linguistic analyses. Also important is to bear in mind is that neither linguistic morphology nor lemmas/lemmata doesn't/don't have that long of a history.
Thanks for being open-minded enough to read this far.
Best Ada
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