Triple

T520136
Position Surface form Disambiguated ID Type / Status
Subject Matsubara E10795 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Habikino E73678 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: Habikino | Statement: [Matsubara, hasNeighbouringMunicipality, Habikino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Habikino
Context triple: [Matsubara, hasNeighbouringMunicipality, Habikino]
  • A. Habikino chosen
    Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
  • B. Kawki
    Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
  • C. Kitchawan
    Kitchawan is a small hamlet within the town of Yorktown in Westchester County, New York, known for its residential character and proximity to natural areas.
  • D. Takatsuki
    Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
  • E. Asokoro
    Asokoro is an upscale residential and administrative district in Abuja, Nigeria, known for hosting many government institutions, embassies, and high-profile residents.
  • 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_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1a00a6c8190a62dc7c901c2f2ff completed Feb. 28, 2026, 1:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a518bfaed48190b03343e0a4a85c89 completed March 2, 2026, 4:57 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.