Triple

T14203441
Position Surface form Disambiguated ID Type / Status
Subject Mayor of Uruma E352022 entity
Predicate seat P75 FINISHED
Object Uruma City Hall E352020 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: Uruma City Hall | Statement: [Mayor of Uruma, seat, Uruma City Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uruma City Hall
Context triple: [Mayor of Uruma, seat, Uruma City Hall]
  • A. Uruma City Hall chosen
    Uruma City Hall is the main municipal government building and administrative center serving the city of Uruma in Okinawa Prefecture, Japan.
  • B. Urayasu City Hall
    Urayasu City Hall is the municipal government building and administrative center responsible for providing public services and local governance for the city of Urayasu in Chiba Prefecture, Japan.
  • C. Hamura City Hall
    Hamura City Hall is the main municipal government building and administrative center serving the city of Hamura in Tokyo, Japan.
  • D. Urasoe City Hall
    Urasoe City Hall is the main municipal government building and administrative center serving the city of Urasoe in Okinawa, Japan.
  • E. Hadano City Hall
    Hadano City Hall is the main municipal government building and administrative center serving the city of Hadano in Kanagawa Prefecture, Japan.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61f589a08190b71ad4e69d92ffd0 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd1951421c81908959634e66857b61 completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:05 a.m.