Triple

T15398072
Position Surface form Disambiguated ID Type / Status
Subject 何叔衡 E368232 entity
Predicate 活动地区 P65106 FINISHED
Object 上海 E5256 NE FINISHED

How this triple was built (2 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: 上海 | Statement: [何叔衡, 活动地区, 上海]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 上海
Context triple: [何叔衡, 活动地区, 上海]
  • A. Shanghai chosen
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • B. Shanghai
    Shanghai is a major Ethereum network upgrade that introduced key changes such as enabling staked ETH withdrawals and improving the protocol’s efficiency and flexibility.
  • C. Shanghai
    Shanghai is an unincorporated community located in Berkeley County, West Virginia, United States.
  • D. Changning City
    Changning City is a county-level city in Hunan Province, China, administered by the prefecture-level city of Hengyang.
  • E. Zhoushan City
    Zhoushan City is a prefecture-level port city in Zhejiang Province, China, comprising a large archipelago and serving as a major maritime and fishing hub in the East China Sea.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e8c5d40819086622b70edcb6294 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff13542c908190abf765b0530c76ce completed May 9, 2026, 10:58 a.m.
Created at: April 10, 2026, 3:19 a.m.