Triple

T15605655
Position Surface form Disambiguated ID Type / Status
Subject German concession in Hankou E375153 entity
Predicate locatedIn P40 FINISHED
Object Hankou E1137206 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: Hankou | Statement: [German concession in Hankou, locatedIn, Hankou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hankou
Context triple: [German concession in Hankou, locatedIn, Hankou]
  • A. Hankou chosen
    Hankou is a historic commercial and port city that now forms one of the three main towns of modern Wuhan in central China.
  • B. Wuhan
    Wuhan is a major city in central China, known as a key industrial, commercial, and transportation hub located at the confluence of the Yangtze and Han rivers.
  • C. Huangzhou
    Huangzhou is the central urban district and administrative heart of Huanggang in Hubei Province, China.
  • D. Huangpi
    Huangpi is a district in Wuhan, Hubei Province, China, historically part of the Qing Empire and known today as a suburban area combining urban development with rural landscapes.
  • E. Yichang
    Yichang is a key city in western Hubei, China, best known as the gateway to the Three Gorges region and the nearby Three Gorges Dam on the Yangtze 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e7d9328819090e93d55881269a5 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56d3541c8190a5a2aa9730260562 completed May 9, 2026, 3:46 p.m.
Created at: April 10, 2026, 4:12 a.m.