Triple

T6978217
Position Surface form Disambiguated ID Type / Status
Subject Yantai E161767 entity
Predicate hasCountyLevelCity P27799 FINISHED
Object Qixia E448647 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: Qixia | Statement: [Yantai, hasCountyLevelCity, Qixia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Qixia
Context triple: [Yantai, hasCountyLevelCity, Qixia]
  • A. Qixia chosen
    Qixia is a county-level city in eastern China’s Shandong province, known for its apple production and scenic hilly landscapes.
  • B. Xishan
    Xishan is the given name of Yan Xishan, a prominent Chinese warlord and political leader active in Shanxi during the early 20th century.
  • C. Xitang
    Xitang is an ancient water town in eastern China renowned for its well-preserved canals, stone bridges, and traditional architecture.
  • D. Sanxiantai
    Sanxiantai is a scenic coastal area and small offshore island in eastern Taiwan, famous for its arched footbridge, unique rock formations, and rich marine ecology.
  • E. Xiong Xiling
    Xiong Xiling was a Chinese politician and philanthropist who briefly served as a reform-minded early premier of the Republic of China during the turbulent early 20th century.
  • 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_69c68854a0d88190bc0bf82263f1afce completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db68d25c8190a1776908619ad979 completed March 27, 2026, 7:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761b614e88190877455edd5f64cf1 completed March 28, 2026, 5:05 a.m.
Created at: March 27, 2026, 2:31 p.m.