Triple

T1434459
Position Surface form Disambiguated ID Type / Status
Subject Namba Hips E30526 entity
Predicate district P2709 FINISHED
Object Namba E4490 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: Namba | Statement: [Namba Hips, district, Namba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namba
Context triple: [Namba Hips, district, Namba]
  • A. Namba chosen
    Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
  • B. Numata
    Numata is a city in Gunma Prefecture, Japan, known as a gateway to the Mount Akagi and Oze National Park areas.
  • C. Kanuma
    Kanuma is a regional harvest festival celebrated mainly in Andhra Pradesh and Telangana as part of the multi-day Makar Sankranti festivities, focusing on cattle worship and agricultural prosperity.
  • D. Namaka
    Namaka is the smaller and inner of the two known moons orbiting the dwarf planet Haumea in the Kuiper Belt.
  • E. Namba Marui
    Namba Marui is a major Marui department store and shopping complex located in Osaka’s bustling Namba district, known for its fashion, dining, and entertainment options.
  • 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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c500a9888190a16fbb1ec97a79c9 completed March 1, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad159e53e88190a566347150e9b4bc completed March 8, 2026, 6:22 a.m.
Created at: March 1, 2026, 8 p.m.