Triple

T17442843
Position Surface form Disambiguated ID Type / Status
Subject 马鞍山 E424699 entity
Predicate hasScenicArea P29946 FINISHED
Object 采石矶风景区
采石矶风景区是位于安徽省马鞍山市长江岸边、以奇峭江崖、古迹遗存和李白诗酒文化闻名的历史文化风景名胜区。
E424699 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 采石矶风景区 | Statement: [马鞍山, hasScenicArea, 采石矶风景区]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 采石矶风景区
Context triple: [马鞍山, hasScenicArea, 采石矶风景区]
  • A. 云龙山
    云龙山是一座位于中国的山岳景区,以秀美的自然风光和人文景观而闻名。
  • B. 慈湖
    慈湖 is a scenic lake in Taiwan known for its tranquil natural surroundings and historical significance as the site of the Cihu Mausoleum of former President Chiang Kai-shek.
  • C. 马鞍山
    马鞍山是位于中国安徽省东部、长江沿岸的一座以钢铁工业和山水景观著称的地级市。
  • D. 武当山
    武当山是位于中国湖北省的著名道教名山和世界文化遗产,以其古建筑群和武当武术而闻名。
  • E. 香山公园
    香山公园 is a historic imperial garden and popular scenic park in Beijing, famed for its wooded hills, autumn foliage, and traditional Chinese pavilions and temples.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 采石矶风景区
Triple: [马鞍山, hasScenicArea, 采石矶风景区]
Generated description
采石矶风景区是位于安徽省马鞍山市长江岸边、以奇峭江崖、古迹遗存和李白诗酒文化闻名的历史文化风景名胜区。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 采石矶风景区
Target entity description: 采石矶风景区是位于安徽省马鞍山市长江岸边、以奇峭江崖、古迹遗存和李白诗酒文化闻名的历史文化风景名胜区。
  • A. 云龙山
    云龙山是一座位于中国的山岳景区,以秀美的自然风光和人文景观而闻名。
  • B. 慈湖
    慈湖 is a scenic lake in Taiwan known for its tranquil natural surroundings and historical significance as the site of the Cihu Mausoleum of former President Chiang Kai-shek.
  • C. 马鞍山 chosen
    马鞍山是位于中国安徽省东部、长江沿岸的一座以钢铁工业和山水景观著称的地级市。
  • D. 武当山
    武当山是位于中国湖北省的著名道教名山和世界文化遗产,以其古建筑群和武当武术而闻名。
  • E. 香山公园
    香山公园 is a historic imperial garden and popular scenic park in Beijing, famed for its wooded hills, autumn foliage, and traditional Chinese pavilions and temples.
  • F. None of above.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44ff927ec8190995798f569e913ba completed April 19, 2026, 3:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01aff63d688190b8fa63c8edafc01c completed May 11, 2026, 10:31 a.m.
NEDg Description generation batch_6a01b0a265348190a884a58f3caf54df completed May 11, 2026, 10:34 a.m.
NED2 Entity disambiguation (via description) batch_6a01b1b0553c8190bb76969fe95154ff completed May 11, 2026, 10:38 a.m.
Created at: April 10, 2026, 5:47 a.m.