Triple

T9889836
Position Surface form Disambiguated ID Type / Status
Subject Guanzhong region E181424 entity
Predicate containsCity P294 FINISHED
Object Baoji E221560 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: Baoji | Statement: [Guanzhong region, containsCity, Baoji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baoji
Context triple: [Guanzhong region, containsCity, Baoji]
  • A. Baoji chosen
    Baoji is a major industrial and transportation hub city in western Shaanxi Province, China, known for its manufacturing base and historical sites.
  • B. Tongchuan
    Tongchuan is a prefecture-level city in central Shaanxi Province, China, historically known for its coal mining industry and location on the Loess Plateau.
  • C. Xianyang
    Xianyang was the capital city of the Qin dynasty and a major political and cultural center in ancient China.
  • D. 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.
  • E. Shangluo
    Shangluo is a prefecture-level city in southeastern Shaanxi, China, known for its mountainous terrain, rich natural resources, and historical sites.
  • 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_69ca8283a6708190801af7a25a7ebb9f completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb47dfa908190884e96e5e5d6f41f completed April 2, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2577794d081909e852bda46f62988 completed April 5, 2026, 12:37 p.m.
Created at: March 30, 2026, 8:39 p.m.