Triple

T3942336
Position Surface form Disambiguated ID Type / Status
Subject Lu’an E92062 entity
Predicate borders P224 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: [Lu’an, borders, Hefei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hefei
Context triple: [Lu’an, borders, 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. Bengbu
    Bengbu is a mid-sized industrial and transportation hub city in eastern China, located in the northern part of Anhui province along the Huai River.
  • 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_69aed965502c8190904ebad1203a4ae8 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedff736c8190b22e03d94c40f61a completed March 9, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b533912bf881909e5e5e9e4245edbf completed March 14, 2026, 10:08 a.m.
Created at: March 9, 2026, 3:24 p.m.