Triple

T19593485
Position Surface form Disambiguated ID Type / Status
Subject Wei He E470293 entity
Predicate majorCityOnRiver P316 FINISHED
Object Baoji NE NERFINISHED

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: [Wei He, majorCityOnRiver, Baoji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baoji
Context triple: [Wei He, majorCityOnRiver, 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 (2 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640782e2c8190b5baef07a2bdd015 completed April 20, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:43 p.m.