nifWrapper
The NLP Interchange Format (NIF) is a RDF/OWL-based format wich allows the spotting of words from text corpora and its metada such as part-of-speech tags, knowledge-base links, entity type, etc. Likewise other Python libraries (e.g., pynif), this library transform NIF data to python classes in order to better proccessing this information.
If you want to create/visualizate NIF data see NIFify in GitHub or a demo.
Example
Install first the library:
pip install nifwrapper
and then, try:
from nifwrapper import *
gold_ttl = '''
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix nif: <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#> .
@prefix itsrdf: <http://www.w3.org/2005/11/its/rdf#> .
<https://example.org/doc1>
a nif:String , nif:Context , nif:RFC5147String ;
nif:isString """Kiev is an important industrial, scientific, educational and cultural center of Eastern Europe."""^^xsd:string ;
nif:beginIndex "0"^^xsd:nonNegativeInteger ;
nif:endIndex "95"^^xsd:nonNegativeInteger ;
nif:sourceUrl <https://example.org/doc1> .
<https://example.org/doc1#char=0,95>
a nif:String , nif:Context , nif:RFC5147String ;
nif:isString """Kiev is an important industrial, scientific, educational and cultural center of Eastern Europe."""^^xsd:string ;
nif:beginIndex "0"^^xsd:nonNegativeInteger ;
nif:endIndex "95"^^xsd:nonNegativeInteger ;
nif:broaderContext <https://example.org/doc1> .
<https://example.org/doc1#char=0,4>
a nif:String , nif:Context , nif:Phrase , nif:RFC5147String ;
nif:referenceContext <https://example.org/doc1#char=0,95> ;
nif:context <https://example.org/doc1> ;
nif:anchorOf """Kiev"""^^xsd:string ;
nif:beginIndex "0"^^xsd:nonNegativeInteger ;
nif:endIndex "4"^^xsd:nonNegativeInteger ;
itsrdf:taIdentRef <https://en.wikipedia.org/wiki/Kiev> .
<https://example.org/doc1#char=33,43>
a nif:String , nif:Context , nif:Phrase , nif:RFC5147String ;
nif:referenceContext <https://example.org/doc1#char=0,95> ;
nif:context <https://example.org/doc1> ;
nif:anchorOf """scientific"""^^xsd:string ;
nif:beginIndex "33"^^xsd:nonNegativeInteger ;
nif:endIndex "43"^^xsd:nonNegativeInteger ;
itsrdf:taIdentRef <https://en.wikipedia.org/wiki/Education> .
<https://example.org/doc1#char=45,56>
a nif:String , nif:Context , nif:Phrase , nif:RFC5147String ;
nif:referenceContext <https://example.org/doc1#char=0,95> ;
nif:context <https://example.org/doc1> ;
nif:anchorOf """educational"""^^xsd:string ;
nif:beginIndex "45"^^xsd:nonNegativeInteger ;
nif:endIndex "56"^^xsd:nonNegativeInteger ;
itsrdf:taIdentRef <https://en.wikipedia.org/wiki/Education> .
<https://example.org/doc1#char=80,94>
a nif:String , nif:Context , nif:Phrase , nif:RFC5147String ;
nif:referenceContext <https://example.org/doc1#char=0,95> ;
nif:context <https://example.org/doc1> ;
nif:anchorOf """Eastern Europe"""^^xsd:string ;
nif:beginIndex "80"^^xsd:nonNegativeInteger ;
nif:endIndex "94"^^xsd:nonNegativeInteger ;
itsrdf:taIdentRef <https://en.wikipedia.org/wiki/Eastern_Europe> .
'''
## ---- parsing
parser = NIFParser()
wrp_gold = parser.parser_turtle(gold_ttl)
## ---- displaying turtle format
print(wrp_gold.toString())
## --- Benchmark
# - inline NIF corpus creation
wrp_sys = NIFWrapper()
doc = NIFDocument("https://example.org/doc1")
#--
sent = NIFSentence("https://example.org/doc1#char=0,95")
sent.addAttribute("nif:isString","Kiev is an important industrial, scientific, educational and cultural center of Eastern Europe.","xsd:string")
sent.addAttribute("nif:broaderContext",["https://example.org/doc1"],"URI LIST")
#--
a1 = NIFAnnotation("https://example.org/doc1#char=0,4", "0", "4", ["https://en.wikipedia.org/wiki/Kiev"], ["dbo:Place"])
a1.addAttribute("nif:anchorOf","Kiev","xsd:string")
a1.addAttribute("ex:newPredicate","This is a test","xsd:string")
sent.pushAnnotation(a1)
#--
a2 = NIFAnnotation("https://example.org/doc1#char=45,56", "45", "56", ["https://en.wikipedia.org/wiki/University"], ["dbo:Organization"])
a2.addAttribute("nif:anchorOf","educational","xsd:string")
sent.pushAnnotation(a2)
#--
a3 = NIFAnnotation("https://example.org/doc1#char=80,94", "80", "94", ["https://en.wikipedia.org/wiki/Eastern_Europe"], ["dbo:Organization"])
a3.addAttribute("nif:anchorOf","Eastern Europe","xsd:string")
sent.pushAnnotation(a3)
#--
doc.pushSentence(sent)
wrp_sys.pushDocument(doc)
## Quality Evaluation
bmk = NIFBenchmark(wrp_sys, wrp_gold)
print(bmk.microF())
Metadata
Release files for nifwrapper 1.6.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nifwrapper-1.6.3.tar.gz | 34.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nifwrapper-1.6.3-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 68.0 kB
Release files / nifwrapper-1.6.3.tar.gz
| Download URL | nifwrapper-1.6.3.tar.gz |
|---|---|
| Size | 34.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
5c084885b09bf882528d7b875e0ab2b6eeaab86f483484c32fdee95001ae0795
|
|
BLAKE2b-256 checksum How to use checksums |
5b351cbe5007046f0de96d9992c0d63402c53334bbf41bccd529205e73e93d60
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.6.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.52.0 CPython/3.8.5
|
Release files / nifwrapper-1.6.3-py2.py3-none-any.whl
| Download URL | nifwrapper-1.6.3-py2.py3-none-any.whl |
|---|---|
| Size | 33.1 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
e916d3ef31b55df242bc5063a4aed3567c22d1037cd64bcaabc2d382b78e6133
|
|
BLAKE2b-256 checksum How to use checksums |
f5354f231f45abe636060008b7fbef0bc3d1037a5eda99e1a7a7be4027c256ae
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.6.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.52.0 CPython/3.8.5
|