Triple

T6177377
Position Surface form Disambiguated ID Type / Status
Subject Xijing E137853 entity
Predicate hasChineseName P4878 FINISHED
Object 西京 E157600 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: 西京 | Statement: [Xijing, hasChineseName, 西京]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 西京
Context triple: [Xijing, hasChineseName, 西京]
  • A. 鳳翔
    鳳翔 was the Imperial Japanese Navy’s Hōshō, the world’s first purpose-built aircraft carrier to enter service.
  • B. Baoji
    Baoji is a major industrial and transportation hub city in western Shaanxi Province, China, known for its manufacturing base and historical sites.
  • C. Shangluo
    Shangluo is a prefecture-level city in southeastern Shaanxi, China, known for its mountainous terrain, rich natural resources, and historical sites.
  • D. Xianyang, China chosen
    Xianyang is a historic city in Shaanxi Province, China, known as the former capital of the Qin dynasty and located near the modern metropolis of Xi’an.
  • E. Hanzhong
    Hanzhong is a historic prefecture-level city in southwestern Shaanxi, China, known as a key gateway between northern and southern China and for its rich cultural and natural landscapes.
  • 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_69c008a80f748190ba3d07ffc81acb29 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05dc87bc48190834042d9c41d5b86 completed March 22, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141bb426881908d5a1451b3619f03 completed March 23, 2026, 1:35 p.m.
Created at: March 22, 2026, 4:18 p.m.