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familienarchiv/nlp-service/extractor.py

89 lines
2.6 KiB
Python

from __future__ import annotations
import re
from datetime import date
import dateparser
import spacy
from spacy.language import Language
from models import ParseResponse
# ── Language model registry ──────────────────────────────────────────────────
_MODEL_NAMES: dict[str, str] = {
"de": "de_core_news_sm",
"en": "en_core_web_sm",
"es": "es_core_news_sm",
}
_nlp_cache: dict[str, Language] = {}
def get_nlp(lang: str) -> Language:
if lang not in _MODEL_NAMES:
raise ValueError(f"Unsupported language: {lang!r}. Valid: {list(_MODEL_NAMES)}")
if lang not in _nlp_cache:
_nlp_cache[lang] = spacy.load(_MODEL_NAMES[lang])
return _nlp_cache[lang]
def load_all_models() -> None:
for lang in _MODEL_NAMES:
get_nlp(lang)
# ── Step 1: Person name extraction ──────────────────────────────────────────
def extract_person_names(doc) -> list[str]:
"""Return PER entity texts in left-to-right span order."""
return [ent.text for ent in doc.ents if ent.label_ == "PER"]
# ── Step 2: Role detection ───────────────────────────────────────────────────
_SENDER_PREPS: dict[str, frozenset[str]] = {
"de": frozenset({"von", "vom"}),
"en": frozenset({"from", "by"}),
"es": frozenset({"de", "por"}),
}
_RECEIVER_PREPS: dict[str, frozenset[str]] = {
"de": frozenset({"an", "nach", "für"}),
"en": frozenset({"to", "for"}),
"es": frozenset({"para", "a"}),
}
def detect_person_role(doc, per_spans: list, lang: str) -> str:
"""Return 'sender', 'receiver', or 'any'.
Only meaningful for single-PER queries — two-person queries always return
'any' because Java derives direction from list position.
"""
if len(per_spans) != 1:
return "any"
span = per_spans[0]
root = span.root
sender = _SENDER_PREPS[lang]
receiver = _RECEIVER_PREPS[lang]
# Primary: dependency-tree children of the PER root
for child in root.children:
if child.dep_ in ("case", "prep", "mo"):
if child.lower_ in sender:
return "sender"
if child.lower_ in receiver:
return "receiver"
# Fallback: token immediately before the span start
if span.start > 0:
prev = doc[span.start - 1]
if prev.lower_ in sender:
return "sender"
if prev.lower_ in receiver:
return "receiver"
return "any"