dumitrescustefan / ronec Goto Github PK

Hi,

When I try to download RONEC copus by running:
python3 -m spacy download ro_core_news_sm
I am getting the following error:
No compatible models found for v2.3.4 of spaCy
This happens also when I try to follow the download commands from this link.

On a second note, I would like to thank you for your work in bringing the RONEC corpus to the world, any of your guidance would be much appreciated.

Hi,

I tried to use spacy with RONEC to check if some contact phone names are person's names or not, and I got weird results:

nlp = spacy.load("ro_core_news_sm")
doc = 'Digi24'
doc = nlp(doc)
for ent in doc.ents:
    print(ent.text, ent.start_char, ent.end_char, ent.label_)
(out): Digi24 0 6 PERSON

It gave me the same results for Pizza Zimbru, BRD, Analize, Vox Roaming...
My Spacy version is '3.0.0rc2'.

Is it a normal behavior or I am not using it correctly?

Hello,

I ve tried to use RONEC in SpaCy for the following legal text from Romanian Official Gazette:

"Aprobă revocarea din calitatea de cenzor a următoarelor persoane: IORGA RADU-GABRIEL,GUCEANU DORINA și TEAHA RODICA și aprobă numirea în calitate de auditor financiar al societatii ARYA CONSULTING S.R.L.,CUI 41617624,J23/3968/2019, pentru o perioadă de 2 ani."

..and I ve got the following result:

persoane 56 64 PERSON
IORGA RADU 66 76 ORGANIZATION
GABRIEL 77 84 ORGANIZATION
TEAHA RODICA 103 115 ORGANIZATION
ARYA CONSULTING S.R.L.,CUI 181 209 ORGANIZATION
41617624,J23/3968/2019 209 231 NUMERIC_VALUE
2 ani 254 259 DATETIME

I am guessing the legal text from Official Gazette looks very different from the one in RONEC . Would I need to create a completely new annotated corpus from Official Gazette or just add to the existing RONEC more annotated legal stuff?

Thanks,
Mihai

Hello,

I attempted to use the RONEC corpus with Spacy for NER and I encountered some problems while following the tutorial for using Spacy with RONEC:

1

I cloned the repository and I tried to obtain the .json train and dev files using the convert_conllubio.py script and Spacy's convert tool as shown in the tutorial:

!python3 ronec/spacy/train-local-model/convert_conllubio.py ronec/ronec/conllup/raw/ronec.conllup .

!python -m spacy convert train_ronec.conllubio . --converter conllubio

When I ran the second command, for the train data set I got this error:

Traceback (most recent call last):
File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/usr/lib/python3.6/runpy.py", line 85, in run_code
exec(code, run_globals)
File "/usr/local/lib/python3.6/dist-packages/spacy/main.py", line 33, in
plac.call(commands[command], sys.argv[1:])
File "/usr/local/lib/python3.6/dist-packages/plac_core.py", line 367, in call
cmd, result = parser.consume(arglist)
File "/usr/local/lib/python3.6/dist-packages/plac_core.py", line 232, in consume
return cmd, self.func(*(args + varargs + extraopts), **kwargs)
File "/usr/local/lib/python3.6/dist-packages/spacy/cli/convert.py", line 106, in convert
no_print=no_print,
File "/usr/local/lib/python3.6/dist-packages/spacy/cli/converters/conllu2json.py", line 25, in conllu2json
for i, (raw_text, tokens) in enumerate(conll_tuples):
File "/usr/local/lib/python3.6/dist-packages/spacy/cli/converters/conllu2json.py", line 68, in read_conllx
id, word, lemma, pos, tag, morph, head, dep, _1, iob = parts
ValueError: too many values to unpack (expected 10)

When I looked at the train_ronec.conllubio file, I noticed that there were 11 columns on the first line instead of 10, as shown below:

1 Tot tot ADV Rp _ 3 advmod _ _ *

I found that deleting the "*" on the first line solved this problem, but I couldn't really understand why this happened.

2

By observing the .json dev and train output files, I noticed that the "ner" field was missing from the train file.
Here is the representation of a word from the dev file:

{
"id":0,
"orth":"Tinerii",
"tag":"Ncmpry",
"head":35,
"dep":"nsubj:pass",
"ner":"U-PERSON"
}

Here is a representation of a word from the train file:

{
"id":35,
"orth":"ROMANIA",
"tag":"Np",
"head":-2,
"dep":"nmod"
}

3

I moved on with the tutorial and I attempted to train the open-source BILSTM-CNN model found here: https://github.com/kamalkraj/Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs with Spacy's train tool. I cloned the repo and I used the command below to train:

!python3 -m spacy train ro Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs/models/ train_ronec.json dev_ronec.json -p ner

I noticed a very strange behavior for this: the model got stuck at 36%, no matter how much time I let it run. This is the output I got:

Training pipeline: ['ner']
Starting with blank model 'ro'
Counting training words (limit=0)
Itn NER Loss NER P NER R NER F Token % CPU WPS
36% 58105/159192 [00:10<00:16, 6216.60it/s]

I tried a few more times and the behavior did not change: it always stopped progressing at around 30-36%. Since it did not return any errors, I am not sure how to debug it, or if I am using it right.

Environment

I am running this on Google Colab. Here is some information about the environment:

• spaCy version:** 2.2.4
• Platform:** Linux-4.19.104+-x86_64-with-Ubuntu-18.04-bionic
• Python version:** 3.6.9

Va salut.
As dori sa folosesc modelul dumneavoastra impreuna cu platforma KNIME si nodul Spacy dar nu stiu cum sa-l descarc de aici si sa-l folosesc in KNIME.
Ma puteti ajuta cumva?
Multumesc!