| from numpy import string_ |
| import re |
|
|
| en_to_ar_camel = { |
| 'B-LOC' : 'مكان', |
| 'B-ORG': 'مؤسسة', |
| 'B-PERS': 'شخص', |
| 'B-MISC': 'معنى بموضوعات متنوعة', |
| 'I-LOC': 'مكان', |
| 'I-ORG': 'مؤسسة', |
| 'I-PERS': 'شحص', |
| 'I-MISC': 'معنى بموضوعات متنوعة', |
| } |
|
|
| en_to_ar = { |
| "B-Artist" : "فنان", |
| "I-Artist" :"فنان", |
| "B-Sound": "صوت", |
| "I-Sound":"صوت", |
| "B-Educational": "تعليمي", |
| "I-Educational":"تعليمي", |
| "B-Building-Grounds":"أراضي البناء", |
| "I-Building-Grounds":"أراضي البناء", |
| "B-Population-Center":"مركز سكني", |
| "B-Nation":"شعب(أمة)", |
| "B-State-or-Province":"ولاية أو مقاطعة", |
| "I-State-or-Province": "ولاية أو مقاطعة", |
| "B-Water-Body": "مسطح مائي", |
| "I-Water-Body":"مسطح مائي", |
| "B-Land-Region-Natural": "أرض طبيعية", |
| "I-Land-Region-Natural":"أرض طبيعية", |
| "B-Software":"سوفتوير(برمجيات)", |
| "I-Software":"سوفتوير(برمجيات)", |
| "B-Scientist": "عالم", |
| "B-Book":"كتاب", |
| "I-Book":"كتاب", |
| "I-Scientist":"عالم", |
| "B-Group":"مجموعة", |
| "B-Celestial":"سماوي", |
| "B-Police":"شرطة", |
| "I-Police":"شرطة", |
| "I-Population-Center":"مركز سكني", |
| "I-Celestial":"سماوي", |
| "B-Engineer":"مهندس", |
| "I-Engineer":"مهندس", |
| "B-Projectile":"قذيفة", |
| "B-Government":"حكومة", |
| "I-Government":"حكومة", |
| "B-Commercial":"تجاري", |
| "I-Commercial":"تجاري", |
| "B-Continent":"قارة", |
| "B-Air":"هواء", |
| "I-Air":"هواء", |
| "B-Other_PER":"شخص", |
| "I-Other_PER":"شخص", |
| "I-Group":"مجموعة", |
| "B-Politician":"سياسي", |
| "I-Politician":"سياسي", |
| "B-Athlete":"رياضي", |
| "I-Athlete":"رياضي", |
| "B-Religious_ORG":"مؤسسة دينية", |
| "I-Religious_ORG":"مؤسسة دينية", |
| "B-Path":"طريق", |
| "I-Path":"طريق", |
| "B-Media":"إعلام", |
| "I-Media":"إعلام", |
| "B-Non-Governmental":"غير حكومي", |
| "I-Non-Governmental":"غير حكومي", |
| "B-County-or-District":"مدينة أو ضاحية", |
| "I-County-or-District":"مدينة أو ضاحية", |
| "B-Businessperson":"رجل أعمال", |
| "B-Lawyer":"محامي", |
| "I-Lawyer":"محامي", |
| "B-GPE-Cluster":"", |
| "I-GPE-Cluster":"", |
| "I-Nation":"شعب(أمة)", |
| "B-Religious_PER":"شخص ديني", |
| "I-Religious_PER":"شخص ديني", |
| "I-Businessperson":"رجل أعمال", |
| "B-Medical-Science":"علوم طبية", |
| "I-Medical-Science":"علوم طبية", |
| "B-Movie":"فيلم", |
| "I-Movie":"فيلم", |
| "B-Water":"ماء", |
| "I-Water":"ماء", |
| "B-Drug":"دواء", |
| "B-Hardware":"عتاد", |
| "I-Hardware":"عتاد", |
| "B-Subarea-Facility":"منشأة منطقة فرعية", |
| "I-Subarea-Facility":"منشأة منطقة فرعية", |
| "B-Blunt":"فظ", |
| "B-Airport":"مطار", |
| "I-Blunt": "فظ", |
| "I-Drug":"دواء", |
| "B-Sports":"رياضة", |
| "I-Sports":"رياضة", |
| "B-Shooting":"رماية", |
| "I-Shooting":"رماية", |
| "B-Food":"طعام", |
| "I-Food":"طعام", |
| "I-Continent":"قارة", |
| "B-Nuclear":"نووي", |
| "I-Nuclear":"نووي", |
| "B-Entertainment":"ترفيه", |
| "I-Entertainment":"ترفيه", |
| "I-Projectile":"قذيفة", |
| "B-Land":"أرض", |
| "B-Sharp":"حاد", |
| "I-Airport":"مطار", |
| "I-Land":"أرض", |
| "B-Plant":"نبات", |
| "I-Plant":"نبات", |
| "B-Exploding":"منفجر", |
| "I-Exploding":"منفجر", |
| "B-Chemical":"كيميائي", |
| "I-Chemical": "كيميائي", |
| } |
|
|
|
|
|
|
|
|
| def get_separate_entities(labels, tokens): |
| """ |
| takes labels and token , return full name entity (mohamed, salah --> "mohamed salah") |
| this will be used to search in wikipedia |
| """ |
| res = [] |
| b_before = False |
| temp = "" |
| key_value = () |
| for i in range(len(labels)): |
| print(res) |
| curr = labels[i] |
| |
| if("B-" in curr): |
| if(b_before): |
| key_value = (temp[:-1], 1) |
| res.append(key_value) |
| temp = tokens[i] + ' ' |
| else: |
| b_before = True |
| temp += tokens[i] + ' ' |
| if(i == len(labels)-1): |
| key_value = (temp[:-1], 1) |
| res.append(key_value) |
| |
|
|
| elif("I-" in curr): |
| temp += tokens[i] + ' ' |
| if(i == len(labels)-1): |
| key_value = (temp[:-1], 1) |
| res.append(key_value) |
|
|
| else: |
| if(temp == ""): |
| key_value = (tokens[i], 0) |
| res.append(key_value) |
| else: |
| key_value = (temp[:-1], 1) |
| res.append(key_value) |
| key_value = (tokens[i], 0) |
| res.append(key_value) |
| temp = "" |
| b_before = False |
| |
| |
|
|
| print(res) |
| return res |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
