Browsing the ELG catalogue

Search the ELG catalogue using Python

from elg import Catalog

First you have to init a catalog object.

catalog = Catalog()

Then you can use the search method to search for resources. This method returns a list of Entity which can be displayed individually. For example, we can search for a Machine Translation service for English and French.

results = catalog.search(
    resource = "Tool/Service", # "Corpus", "Lexical/Conceptual resource" or "Language description"
    function = "Machine Translation", # function should be pass only if resource is set to "Tool/Service"
    languages = ["en", "fr"], # string or list if multiple languages
    limit = 100,
)
print(f"Machine Translation service for English and French:\n{list(results)[0]}")

Machine Translation service for English and French:
----------------------------------------------------------------------
Id             597
Name           Transformer en-fr: Machine Translation Model Trained
               Using Tensor2tensor
Resource type  Tool/Service
Entity type    LanguageResource
Description    Transformer en-fr translation model performs automatic
               translation of raw text from en to fr
Licences       ['Apache License 2.0']
Languages      ['English', 'French']
Status         None
----------------------------------------------------------------------

Another example can be a German NER corpora.

results = catalog.search(
    resource = "Corpus", # "Corpus", "Lexical/Conceptual resource" or "Language description"
    languages = ["German"], # string or list if multiple languages
    search="ner",
    limit = 100,
)
print(f"German corpus for NER:\n{next(results)}")

German corpus for NER:
----------------------------------------------------------------------
Id             5010
Name           GermEval 2014 NER Shared Task
Resource type  Corpus
Entity type    LanguageResource
Description    The data was sampled from German Wikipedia and News
               Corpora as a collection of citations.The dataset covers
               over 31,000 sentences corresponding to over 590,000
               tokens.
Licences       ['Creative Commons Attribution 4.0 International']
Languages      ['German']
Status         None
----------------------------------------------------------------------

You can init a service from an Entity.

We can use the catalog to search a Named Entity Recognizer for French and init a Service with the returned Entity.

catalog = Catalog()

results = catalog.search(
    resource = "Tool/Service",
    function = "Named Entity Recognition",
    languages = ["fr"],
    limit = 1,
)

entity = next(results)
print(entity)

from elg import Service

lt = Service.from_entity(entity=entity)
result = lt("Jean Dupond vit à Paris.")
print(f"\n{result}")

----------------------------------------------------------------------
Id             474
Name           Cogito Discover Named Entity Recognizer
Resource type  Tool/Service
Entity type    LanguageResource
Description    Annotation of entities: People, Organizations, Places,
               Known concepts, Unknown concepts. And also tags: urls,
               mail addresses, phone numbers, addresses, dates, time,
               measures, money, percentage, file folder.
Licences       ['Cogito Discover License']
Languages      ['English', 'German', 'Portuguese', 'Dutch', 'French',
               'Spanish', 'Italian']
Status         None
----------------------------------------------------------------------
Warning: The refresh token will expire in -2520.0 seconds!
Calling:
        [474] Cogito Discover Named Entity Recognizer
with request:
        type: text - content: Jean Dupond vit à Paris. - mimeType: text/plain


type='annotations' warnings=None features=None annotations={'People': [Annotation(start=0, end=11, source_start=None, source_end=None, features={'SURNAME': 'Dupond', 'SEX': 'M', 'name': 'Jean Dupond', 'NAME': 'Jean'})], 'Place': [Annotation(start=18, end=23, source_start=None, source_end=None, features={'Lemma': 'Paris', 'name': 'Paris', 'Glossa': 'capitale in Paris (Île-de-France/France/Europe', 'GEOREF': 'Paris/Île-de-France/France/Europe'})]}