Triple

T14985136
Position Surface form Disambiguated ID Type / Status
Subject Russian concession in Hankou E373680 entity
Predicate location 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: [Russian concession in Hankou, location, Hankou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hankou
Context triple: [Russian concession in Hankou, location, 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6ff4a7c8190ab7554f3a1a09b67 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fed31c0ab08190814c41d852f9f523 completed May 9, 2026, 6:24 a.m.
Created at: April 10, 2026, 2:52 a.m.