# Copyright (c) 2020 EyeOnText, All Rights Reserved.
# NOTICE: All information contained herein is, and remains the property of EyeOnText.
from eot.wowool.native import Language, Domain
from eot.wowool.annotation import Concept
from eot.wowool.error import Error
try:
dutch = Language("dutch")
entities = Domain("dutch-entity")
doc = dutch("Jan Van Den Berg werkte als hoofdarts bij Omega Pharma.")
doc = entities(doc)
# filter some concepts
requested_concepts = set(["Person", "Position", "Company"])
concept_filter = lambda concept: concept.uri in requested_concepts
for concept in Concept.iter(doc.analysis, concept_filter):
print(f"literal: {concept.literal:<20}, stem={concept.stem}")
# flatten concepts into dict
print("-" * 40)
for concept in Concept.iter(doc.analysis, concept_filter):
print({**concept})
print("-" * 40)
for person in Concept.iter(doc.analysis,
lambda concept: concept.uri == "Person"):
for person_parts in Concept.iter(
person, lambda concept: concept.uri.startswith("Person")):
print(
f"Person: {person_parts.uri:<20}, stem={person_parts.literal}")
# Copyright (c) 2020 EyeOnText, All Rights Reserved.
# NOTICE: All information contained herein is, and remains the property of EyeOnText.
from eot.wowool.native import Language, Domain
from eot.wowool.error import Error
try:
english = Language("english")
entities = Domain("english-entity")
doc = english(
"John Smith was in London on the 3/11/2020. He took a cab to the central station."
)
doc = entities(doc)
print('-' * 80)
print(doc)
except Error as ex:
print("Exception:", ex)
"from": {
"uri": "USER"
},
"to": {
"slot": "Document",
"label": "Document"
},
"relation": {
"label": "Mentions"
}
}]
}
# fmt: on
try:
english = Language("dutch")
entities = Domain("dutch-entity")
myrule = Domain(source=""" rule:{ 'user' '\:' {(<>)+}=USER }; """)
doc = english(
"user:John \n\nJan Van Den Berg werkte als hoofdarts bij Omega Pharma."
)
doc = entities(doc)
doc = myrule(doc)
graphit = EntityGraph(graph_config)
graphit.slots["Document"] = {"data": "hello"}
doc = graphit(doc)
results = doc.entity_graph.merge()
print('-' * 80)
print(f'relations : {results.headers}')
import streamlit as st
from eot.wowool.native import Language, Domain
from eot.wowool.topic_identifier import TopicIdentifier
from eot.wowool.annotation import Concept
import pandas as pd
entity_filter = set(["Person", "Company", "Address", "City", "Facility"])
st.write("EyeOnText English Topics and Entities")
name = st.text_area("Enter Your text",
"""John Smith works at EyeOnText in Antwerp.""")
if st.button("Analyze"):
input_text = name
analyzer = Language("english")
entities = Domain("english-entity")
topicit = TopicIdentifier(language="english")
doc = entities(analyzer(input_text))
topics = topicit.get_topics(doc, 20)
# st.write("topics")
# st.write(pd.DataFrame(topics, columns=["topic", "relevancy"]))
combined_topics = {}
for topic in topics:
combined_topics[topic[0]] = ["topic", topic[0], topic[1]]
for concept in Concept.iter(doc,
lambda concept: concept.uri in entity_filter):
combined_topics[concept.literal] = [concept.uri, concept.literal, 1.0]
# Copyright (c) 2020 EyeOnText, All Rights Reserved.
# NOTICE: All information contained herein is, and remains the property of EyeOnText.
from eot.wowool.native import Language, Domain
from eot.wowool.error import Error
from eot.wowool.annotation import Concept
from eot.wowool.annotation import Token
try:
analyzer = Language("swedish")
rule_source = """
// Compound Sample:
// capture all the word with verzekering
lexicon:(input="component"){
försäkring } = INSURANCE_COMPONENT;
// capture only the real verzekering not verzekeringsmaatschapijen
lexicon:(input="head"){
försäkring } = INSURANCE_HEAD;
// capture the cost of the insurance.
rule:{ {h'försäkring'} = INSURANCE_TYPE { Num +currency } = INSURANCE_PRICE };
"""
compounds = Domain(source=rule_source)
input = "Det finns försäkringsbolag 40000 euro och försäkring: bilförsäkring 100 euro, cykelförsäkring 200 SEK "
doc = compounds(analyzer(input))
print(doc)
print("-" * 80)
print(rule_source)
print("-" * 80)
