inflected | A port of ActiveSupport 's inflector to Node.js | Runtime Evironment library

I have a dropdown that onChange I use ajax to load some .json from a method in a controller.

However I am getting error 404 returned

If I remove the .json extension I get error 500 missing template which I have not been able to resolve either. I have tried different solution. I would rather use the .json ext anyway and let cakephp return the correct formatted JSON.

I'm using solr 6.6.0. (and The core was created with "sample") When I importing rich document (here HTML) using ExtractingRequestHandler, unnecessary line feed code(\n) and tab characters(\t) are indexed. I tried setting MappingCharFilterFactory etc, but it was ineffective. I also referred to the following URL, but there was no effect.

How do you prevent tabs and newline codes (\ n, \ r \ n, \ t) from being indexed?

[Steps I took]

1. access to "http://localhost:8983/solr/#/sample/documents"
2. select my core (sample). And click "document" link in left menu.

3. fill the forms

   • Request-Handler "/update/extract"
   • Document Type File Upload
   • Documetn (s) test.html
   • Extracting Req. Handler Params * unspecified
   • Commit Within 1000
   • Overwrite true

4. Select "text.html" above and execute it.

[Response]

I try to lemmatize a text using spaCy 2.0.12 with the French model fr_core_news_sm. Morevoer, I want to replace people names by an arbitrary sequence of characters, detecting such names using token.ent_type_ == 'PER'. Example outcome would be "Pierre aime les chiens" -> "~PER~ aimer chien".

The problem is I can't find a way to do both. I only have these two partial options:

• I can feed the pipeline with the original text: doc = nlp(text). Then, the NER will recognize most people names but the lemmas of words starting with a capital won't be correct. For example, the lemmas of the simple question "Pouvons-nous faire ça?" would be ['Pouvons', '-', 'se', 'faire', 'ça', '?'], where "Pouvons" is still an inflected form.
• I can feed the pipeline with the lower case text: doc = nlp(text.lower()). Then my previous example would correctly display ['pouvoir', '-', 'se', 'faire', 'ça', '?'], but most people names wouldn't be recognized as entities by the NER, as I guess a starting capital is a useful indicator for finding entities.

My idea would be to perform the standard pipeline (tagger, parser, NER), then lowercase, and then lemmatize only at the end.

However, lemmatization doesn't seem to have its own pipeline component and the documentation doesn't explain how and where it is performed. This answer seem to imply that lemmatization is performed independent of any pipeline component and possibly at different stages of it.

So my question is: how to choose when to perform the lemmatization and which input to give to it?

I've recently begun working on a sentiment analysis project on German texts and I'm planning on using a stemmer to improve the results.

NLTK comes with a German Snowball Stemmer and I've already tried to use it, but I'm unsure about the results. Maybe it should be this way, but as a computer scientist and not a linguist, I have a problem with inflected verb forms stemmed to a different stem.

Take the word "suchen" (to search), which is stemmed to "such" for 1st person singular but to "sucht" for 3rd person singular.

I know there is also lemmatization, but no working German lemmatizer is integrated into NLTK as far as I know. There is GermaNet, but their NLTK integration seems to have been aborted.

Getting to the point: I would like inflected verb forms to be stemmed to the same stem, at the very least for regular verbs within the same tense. If this is not a useful requirement for my goal, please tell me why. If it is, do you know of any additional resources to use which can help me achieve this goal?

Edit: I forgot to mention, any software should be free to use for educational and research purposes.

Assume a very large corpus of any inflective language. Does the following make sense? By applying LSA on such corpus, words with similar concepts converge together in vector space, thus inflected word forms reffering to the same concept should ideally be identical with their lemma in the space. With such assumption, any lemmatization or stemming of queries or corpus is not necessary. Or am i totally wrong?

I've seen a few of these questions but the answers never seem to be clear cut. I need to iterate through a javascript object in my pug view. First time using pug, so I may be missing something obvious.

Controller:

this is a fragment of my database. Model

I used CakePHP 3.0 Bake command to create controllers, models and views. As you see I got a HABTM association but also it has an attribute. I can insert data using the BOM view and the proceso view. But, when I try to edit the time associated with these things I got the message

Record not found in table "bom_proceso" with primary key ['1']

I need to edit that attribute and I don't know how to do with that error or if I made something wrong.

BomProcesoTable Model

I have a first TEI which content is used for XSLT that you can find here http://xsltfiddle.liberty-development.net/3Nqn5Y4/7

A second TEI in corpus_ilimilku.xml which I need to use in the same XSLT file:

Following this post Compare variable in preceding-sibling with current node, I tried to compare current node in order to remove duplicate occurrences.