Triple

T6818520
Position Surface form Disambiguated ID Type / Status
Subject Min River E156833 entity
Predicate flowsThrough P225 FINISHED
Object Yibin E279044 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: Yibin | Statement: [Min River, flowsThrough, Yibin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yibin
Context triple: [Min River, flowsThrough, Yibin]
  • A. Yibin chosen
    Yibin is a historic prefecture-level city in southwestern China known as the "First City on the Yangtze River," where the Jinsha and Min rivers converge to form the Yangtze.
  • B. Luzhou
    Luzhou is a prefecture-level city in southern Sichuan, China, known for its historic river port and famous strong-aroma baijiu liquor industry.
  • C. Luzhou
    Luzhou is an old historical name for the city now known as Hefei, the capital of Anhui Province in eastern China.
  • D. Deyang
    Deyang is an industrial city in southwestern China known for its heavy machinery manufacturing and location near Chengdu in Sichuan Province.
  • E. Langzhong
    Langzhong is an ancient county-level city in Sichuan, China, renowned for its well-preserved historic old town and traditional architecture along the Jialing 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_69c688298a288190af3f285d57f76bbe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d355b52081909f037cec76bdccf6 completed March 27, 2026, 6:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7426356a88190a36b53a46c1776e0 completed March 28, 2026, 2:52 a.m.
Created at: March 27, 2026, 2:17 p.m.