Initial travel knowledge graph release
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scripts/kg_schema_v1_preview_from_report.py
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238
scripts/kg_schema_v1_preview_from_report.py
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#!/usr/bin/env python3
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"""Build a kg_schema_v1 preview from the Huaxi extraction comparison report.
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The comparison report intentionally keeps review_status beside each candidate
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for human reading. The production schema is stricter, so this script removes
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review-only fields, derives evidence_links, validates the shape, and writes a
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reviewable summary for discussion before anything is published to the graph.
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"""
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from __future__ import annotations
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import json
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from copy import deepcopy
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from pathlib import Path
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from typing import Any
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ROOT = Path("/Users/xuexue/new2")
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IN_JSON = ROOT / "docs/reports/huaxi_kg_extraction_comparison.json"
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SCHEMA_JSON = ROOT / "app/schemas/kg_extraction_v1.schema.json"
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OUT_JSON = ROOT / "docs/reports/huaxi_kg_schema_v1_ready.json"
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OUT_REVIEW = ROOT / "docs/reports/huaxi_kg_schema_v1_review_plan.md"
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def strip_review_fields(row: dict[str, Any]) -> dict[str, Any]:
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item = deepcopy(row)
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item.pop("review_status", None)
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return item
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def evidence_links_for(target_ref: str, spans: list[dict[str, Any]]) -> list[dict[str, Any]]:
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links: list[dict[str, Any]] = []
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for span in spans or []:
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evidence_id = span.get("evidence_id")
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quote = str(span.get("quote") or "").strip()
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if evidence_id and quote:
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links.append({
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"target_ref": target_ref,
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"evidence_id": evidence_id,
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"support_type": "supports",
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"quote": quote,
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})
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return links
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def statement_ref(row: dict[str, Any], index: int) -> str:
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subj = str(row.get("subject_ref") or "")
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pred = str(row.get("predicate") or "")
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obj = str(row.get("object_ref") or "")[:48]
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return f"stmt_{index:03d}:{subj}:{pred}:{obj}"
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def build_payload(source: dict[str, Any]) -> dict[str, Any]:
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final = source["final"]
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payload = {
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"entities": [strip_review_fields(r) for r in final.get("entities", [])],
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"events": [strip_review_fields(r) for r in final.get("events", [])],
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"concepts": [strip_review_fields(r) for r in final.get("concepts", [])],
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"relations": [strip_review_fields(r) for r in final.get("relations", [])],
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"statements": [strip_review_fields(r) for r in final.get("statements", [])],
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"schema_proposals": [strip_review_fields(r) for r in final.get("schema_proposals", [])],
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"evidence_links": [],
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}
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links: list[dict[str, Any]] = []
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for row in payload["entities"]:
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links.extend(evidence_links_for(row["temp_id"], row.get("source_spans") or []))
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for row in payload["events"]:
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links.extend(evidence_links_for(row["temp_id"], row.get("source_spans") or []))
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for row in payload["concepts"]:
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links.extend(evidence_links_for(row["temp_id"], row.get("source_spans") or []))
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for idx, row in enumerate(payload["statements"], start=1):
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links.extend(evidence_links_for(statement_ref(row, idx), row.get("source_spans") or []))
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seen = set()
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for link in links:
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sig = (link["target_ref"], str(link["evidence_id"]), link["quote"])
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if sig in seen:
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continue
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seen.add(sig)
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payload["evidence_links"].append(link)
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return payload
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def validate_payload(payload: dict[str, Any]) -> str:
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try:
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import jsonschema # type: ignore
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except Exception:
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required = [
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"entities", "events", "concepts", "relations", "statements",
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"schema_proposals", "evidence_links",
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]
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missing = [key for key in required if not isinstance(payload.get(key), list)]
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if missing:
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raise ValueError(f"missing list fields: {missing}")
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for row in payload["entities"]:
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for key in ["temp_id", "name", "entity_type", "confidence"]:
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if key not in row:
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raise ValueError(f"entity missing {key}: {row}")
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for row in payload["events"]:
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for key in ["temp_id", "title", "event_type", "confidence"]:
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if key not in row:
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raise ValueError(f"event missing {key}: {row}")
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for row in payload["concepts"]:
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for key in ["temp_id", "name", "concept_type", "confidence"]:
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if key not in row:
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raise ValueError(f"concept missing {key}: {row}")
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for row in payload["relations"]:
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for key in ["relation_type", "source_type", "target_type", "confidence"]:
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if key not in row:
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raise ValueError(f"relation missing {key}: {row}")
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for row in payload["statements"]:
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for key in ["subject_ref", "predicate", "object_ref", "object_kind", "confidence"]:
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if key not in row:
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raise ValueError(f"statement missing {key}: {row}")
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return "structural check passed"
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schema = json.loads(SCHEMA_JSON.read_text(encoding="utf-8"))
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jsonschema.Draft202012Validator(schema).validate(payload)
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return "valid"
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AUTO_PUBLISH_THRESHOLD = 0.8
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def review_bucket(row: dict[str, Any], kind: str) -> str:
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confidence = float(row.get("confidence") or 0)
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has_disagreement = bool(row.get("model_disagreement") or row.get("conflict"))
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if kind == "schema_proposal":
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if confidence >= AUTO_PUBLISH_THRESHOLD and not has_disagreement:
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return "进入 Schema Proposal 队列：不阻塞数据入图"
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return "人工审核：schema 建议分数低或模型不一致"
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if confidence >= AUTO_PUBLISH_THRESHOLD and not has_disagreement:
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return "自动入候选发布：多模型一致且分数 >= 0.8"
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return "人工审核：模型不一致或最终分数 < 0.8"
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def write_review_plan(raw: dict[str, Any], payload: dict[str, Any], validation: str) -> None:
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counts = {k: len(payload[k]) for k in [
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"entities", "events", "concepts", "relations",
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"statements", "schema_proposals", "evidence_links",
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]}
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lines = [
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"# 花溪公园 kg_schema_v1 效果与人工审核方案",
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"",
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"## 这次新模式会得到什么",
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"",
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f"- Entity：{counts['entities']} 个",
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f"- Event：{counts['events']} 个",
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f"- Concept：{counts['concepts']} 个",
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f"- Relation Schema：{counts['relations']} 个",
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f"- Statement：{counts['statements']} 条",
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f"- Schema Proposal：{counts['schema_proposals']} 条",
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f"- Evidence Link：{counts['evidence_links']} 条",
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f"- JSON Schema 校验：{validation}",
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"",
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"## 和旧 web_agent 软字段模式的差别",
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"",
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"| 维度 | 旧模式 | kg_schema_v1 新模式 |",
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"|---|---|---|",
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"| 抽取目标 | summary/history/features 等软字段 + schema_gaps | Entity/Event/Concept/Relation/Statement 全量候选 |",
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"| 基本信息 | 容易被放进 schema_gaps，不能稳定入图 | 地址、开放时间、门票、面积、等级等变成可入图 Statement |",
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"| 历史信息 | 部分进入 history 文本 | 变成 Event 节点，并通过 HAS_EVENT 连到地点 |",
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"| 推荐语义 | 缺少概念层 | 历史文化、生态公园、亲水游憩等变成 Concept |",
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"| 人工审核 | 主要审候选实体字段 | 审 Entity/Event/Concept/Statement/SchemaProposal，能细粒度放行 |",
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"",
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"## 人工介入规则",
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"",
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"1. 多模型结果一致、证据 quote 可定位、final_score/confidence >= 0.8：自动进入发布候选，可直接写入正式图谱。",
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"2. 多模型结果不一致、存在冲突字段、或 final_score/confidence < 0.8：转人工审核。",
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"3. 新关系、新事件类型、新字段进入 Schema Proposal 队列；它不阻塞事实数据入图，但 schema 是否升级单独治理。",
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"4. 人工只处理低分/冲突/拿不准的数据，不再默认审所有候选。",
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"5. 发布时每条节点和关系保留 evidence_id、quote、confidence，后续可追溯和回滚。",
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"",
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"## 建议入图谱结构",
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"",
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"```cypher",
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"(:Place {id:'ent_huaxi_park', name:'花溪公园'})",
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"(:Event {id:'evt_1937_park_build', event_id:'evt_1937_park_build', title:'花溪正式辟建为公园', event_date:'1937年', event_date_norm:'1937', event_type:'ConstructionEvent', evidence_id, evidence_quote})",
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"(:Concept {id:'cpt_historical_culture', name:'历史文化景区'})",
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"(:Place)-[:HAS_EVENT {event_date, event_type, evidence_id, confidence}]->(:Event)",
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"(:Place)-[:HAS_CONCEPT {evidence_id, confidence}]->(:Concept)",
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"(:Place)-[:HAS_PART {evidence_id, confidence}]->(:ScenicSpot)",
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"(:Place)-[:NEARBY_ATTRACTION {distance_text, evidence_id}]->(:Place)",
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"```",
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"",
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"## 自动发布 / 人工审核判定",
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"",
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"| 类型 | ID/关系 | 名称/内容 | 置信度 | 建议 |",
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"|---|---|---|---:|---|",
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]
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for kind, key, label_key in [
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("entity", "entities", "name"),
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("event", "events", "title"),
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("concept", "concepts", "name"),
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]:
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for row in payload[key]:
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lines.append(
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f"| {kind} | {row.get('temp_id')} | {row.get(label_key)} | "
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f"{float(row.get('confidence') or 0):.2f} | {review_bucket(row, kind)} |"
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)
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for row in payload["schema_proposals"]:
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lines.append(
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f"| schema_proposal | {row.get('proposal_type')} | {row.get('name')} | "
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f"{float(row.get('confidence') or 0):.2f} | {review_bucket(row, 'schema_proposal')} |"
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)
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lines += [
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"",
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"## 当前结论",
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"",
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"花溪公园这份百度百科证据使用 kg_schema_v1 后，已经足够形成一批完整候选知识。",
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"但为了保证城市知识图谱可长期复用，正确做法不是所有条目都人工审，而是：",
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"",
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"```text",
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"Evidence -> kg_schema_v1 多模型抽取 -> 决策合并/评分",
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"-> final_score >= 0.8 且无冲突：自动发布到 FalkorDB",
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"-> final_score < 0.8 或模型冲突：进入人工审核",
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"```",
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"",
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"对应严格 JSON 输出：`/Users/xuexue/new2/docs/reports/huaxi_kg_schema_v1_ready.json`",
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]
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OUT_REVIEW.write_text("\n".join(lines), encoding="utf-8")
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def main() -> None:
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raw = json.loads(IN_JSON.read_text(encoding="utf-8"))
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payload = build_payload(raw)
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validation = validate_payload(payload)
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OUT_JSON.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8")
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write_review_plan(raw, payload, validation)
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print(OUT_JSON)
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print(OUT_REVIEW)
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print({k: len(v) for k, v in payload.items() if isinstance(v, list)})
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print(validation)
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if __name__ == "__main__":
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main()
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