Triple

T4720535
Position Surface form Disambiguated ID Type / Status
Subject Anhui Medical University E104754 entity
Predicate locatedIn P40 FINISHED
Object Hefei E17536 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: Hefei | Statement: [Anhui Medical University, locatedIn, Hefei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hefei
Context triple: [Anhui Medical University, locatedIn, Hefei]
  • A. Hefei chosen
    Hefei is the capital and largest city of Anhui Province in eastern China, known as a major industrial, scientific, and educational center.
  • B. Wuhu
    Wuhu is a major industrial and transportation hub city in southeastern Anhui Province, eastern China, situated on the lower reaches of the Yangtze River.
  • C. Chuzhou
    Chuzhou is a prefecture-level city in eastern China known for its location near the Yangtze River and its role as a regional transportation and agricultural hub in Anhui Province.
  • D. Anqing
    Anqing is a prefecture-level city in southwestern Anhui Province, China, known historically as a regional political and military center along the Yangtze River.
  • E. Chaohu City
    Chaohu City is a county-level city in Anhui Province, China, known for its proximity to the large freshwater Chaohu Lake and its role in regional agriculture and fisheries.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6428e9e081908ce4041183cad13b completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea4623ae881908f5dac4eaa56f91d completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:18 p.m.