Triple

T14900080
Position Surface form Disambiguated ID Type / Status
Subject Kanan E359980 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Taishi E359979 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: Taishi | Statement: [Kanan, neighboringMunicipality, Taishi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taishi
Context triple: [Kanan, neighboringMunicipality, Taishi]
  • A. Taishi chosen
    Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
  • B. Taishi
    Taishi was the first era name used by Emperor Wu of the Western Han dynasty, marking an important early phase of his long and influential reign in ancient China.
  • C. Taihoku
    Taihoku was the Japanese colonial-era name for Taipei, which served as the administrative and political center of Taiwan under Japanese rule.
  • D. Taizi
    Taizi is the traditional Chinese title for the designated heir apparent to the imperial throne.
  • E. Tudigong
    Tudigong is a widely venerated Chinese earth god and local tutelary deity associated with protecting land, villages, and community welfare.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded609bf68819099ca3aa3fe1acadc completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b6a8aac8190ad062b80d384fb14 completed May 8, 2026, 11:02 p.m.
Created at: April 10, 2026, 2:11 a.m.