Triple

T15474592
Position Surface form Disambiguated ID Type / Status
Subject Hebi E376751 entity
Predicate borders P224 FINISHED
Object Xinxiang E214214 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: Xinxiang | Statement: [Hebi, borders, Xinxiang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xinxiang
Context triple: [Hebi, borders, Xinxiang]
  • A. Xinxiang chosen
    Xinxiang is a prefecture-level industrial and transportation hub city located in northern Henan Province, China.
  • B. Xuchang
    Xuchang is a historically significant city in central China, known as a former capital during the Three Kingdoms period and now an important industrial and transportation hub.
  • C. Zhoukou
    Zhoukou is a prefecture-level city in eastern Henan Province, China, known as an important agricultural and transportation hub with historical and cultural significance.
  • D. Zhumadian
    Zhumadian is a prefecture-level city in southern Henan Province, China, known as an important regional transport and agricultural hub.
  • E. Shangqiu
    Shangqiu is a historic prefecture-level city in eastern Henan Province, China, known as one of the country’s ancient capitals and an important regional transportation hub.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6e859481909c3d08343b7ad27c completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff36595bfc8190a0d60b3cb875ccc5 completed May 9, 2026, 1:27 p.m.
Created at: April 10, 2026, 3:34 a.m.