Triple

T9510636
Position Surface form Disambiguated ID Type / Status
Subject Himeji E229381 entity
Predicate sisterCity P1072 FINISHED
Object Yingkou E303634 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: Yingkou | Statement: [Himeji, sisterCity, Yingkou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yingkou
Context triple: [Himeji, sisterCity, Yingkou]
  • A. Yingkou chosen
    Yingkou is a coastal port city in northeastern China’s Liaoning Province, known as an important industrial and shipping hub on the Bohai Sea.
  • B. Panjin
    Panjin is an industrial and oil-producing city in northeastern China, best known for its striking Red Beach wetlands along the Bohai Sea.
  • C. Liaoyuan
    Liaoyuan is a prefecture-level city in northeastern China known for its coal mining history and location in the central part of Jilin Province.
  • D. Jinzhou
    Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
  • E. Dandong
    Dandong is a northeastern Chinese border city on the Yalu River, known as a key gateway for trade and transport between China and North Korea.
  • 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_69ca84777560819084cddd999badc1aa completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9868616c8190856f89fecfa1a02e completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a31600c8190a4a7ecb5231caa36 completed April 4, 2026, 4:20 p.m.
Created at: March 30, 2026, 7:58 p.m.