| import streamlit as st | |
| import streamlit.components.v1 as components | |
| import requests | |
| import hashlib | |
| from entity_extraction import extract_entities | |
| st.title('Entity Linking Demo') | |
| st.markdown("""Linking named entities in an article to | |
| wikidata entries (allowing us to pull the images). | |
| *Note: Only trained on entities before May 2020*""") | |
| article = st.text_area('Article to analyze:', value=open("example.txt").read()) | |
| if st.button('Submit'): | |
| with st.spinner(text="Extracting..."): | |
| good_ents = [] | |
| ents = extract_entities(article) | |
| for i, ent in enumerate(ents): | |
| r = requests.get("https://www.wikidata.org/w/api.php?action=wbgetclaims&format=json&property=P18&entity=" + ent._.kb_qid) | |
| data = r.json()["claims"] | |
| if "P18" in data.keys(): | |
| data = data["P18"][0]["mainsnak"] | |
| img_name = data["datavalue"]["value"].replace(" ", "_") | |
| img_name_hash = hashlib.md5(img_name.encode("utf-8")).hexdigest() | |
| a = img_name_hash[0] | |
| b = img_name_hash[1] | |
| url= f"https://upload.wikimedia.org/wikipedia/commons/{a}/{a}{b}/{img_name}" | |
| good_ents.append((ent.text, ent.label_, ent._.kb_qid, ent._.url_wikidata, ent._.nerd_score, url)) | |
| cols = st.columns(len(good_ents)) | |
| for i, ent in enumerate(good_ents): | |
| with cols[i]: | |
| components.html(f"<image style='border-radius: 50%;object-fit:cover;width:100px;height:100px' src='{ent[-1]}'/>", height=110, width=110) | |
| st.caption(ent[0]) | |