Named Entity Matching and Extraction (NEMEX) is a python package for approximate entity extraction. Currently, it is mainly based on Faerie [1] algorithm.
Soon as:
pip install nemexHere we show a simple example to extract entities from a pre-defined dictionary.
from nemex import Nemex
import json
E = [
"kaushik ch",
"chakrabarti",
"chaudhuri",
"venkatesh",
"surajit ch"
]
D = "an efficient filter for approximate membership checking. venkaee shga kamunshik kabarati, dong xin, surauijt chadhurisigmod."
nemex = Nemex(E) # initialize with dictionar
output = nemex(D) # query document
print(json.dumps(output, indent=2))Running the example gives results as:
{
"document": "an efficient filter for approximate membership checking. venkaee shga kamunshik kabarati, dong xin, surauijt chadhurisigmod.",
"matches": [
{
"valid": true,
"entity": [
"chaudhuri",
2
],
"score": 2,
"match": " chadhuri",
"span": [
108,
117
]
},
{
"valid": true,
"entity": [
"chaudhuri",
2
],
"score": 1,
"match": "chadhuri",
"span": [
109,
117
]
},
{
"valid": true,
"entity": [
"chaudhuri",
2
],
"score": 2,
"match": "chadhuris",
"span": [
109,
118
]
},
{
"valid": true,
"entity": [
"chaudhuri",
2
],
"score": 2,
"match": "hadhuri",
"span": [
110,
117
]
},
{
"valid": true,
"entity": [
"venkatesh",
3
],
"score": 2,
"match": "venkaee sh",
"span": [
57,
67
]
},
{
"valid": true,
"entity": [
"surajit ch",
4
],
"score": 2,
"match": "surauijt ch",
"span": [
100,
111
]
}
]
}The authors of Faerie [1] released the binary for the code, which was written in C++. The first open-source version, called NEMEX, was originally written in Java by Günter Neumann and then maintained partly by Amir Moin at DFKI, Saarbrücken.
[1] Li, G., Deng, D., & Feng, J. (2011, June). Faerie: efficient filtering algorithms for approximate dictionary-based entity extraction. In Proceedings of the 2011 ACM SIGMOD International Conference on Management of data (pp. 529-540). ACM.
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