Triple

T3014273
Position Surface form Disambiguated ID Type / Status
Subject Naniwa-ku E82297 entity
Predicate hasNeighbouringWard P45005 FINISHED
Object Abeno-ku E152381 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: Abeno-ku | Statement: [Naniwa-ku, hasNeighbouringWard, Abeno-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abeno-ku
Context triple: [Naniwa-ku, hasNeighbouringWard, Abeno-ku]
  • A. Abeno district chosen
    Abeno district is a major commercial and residential area in Osaka, Japan, known for its large shopping complexes and the landmark Abeno Harukas skyscraper.
  • B. Nishi-ku
    Nishi-ku is a ward in Fukuoka, Japan, known for its coastal areas, residential neighborhoods, and access to both urban amenities and natural scenery.
  • C. Nishi-ku
    Nishi-ku is a central ward of Yokohama, Japan, known as a major commercial and business district that includes the Minato Mirai 21 waterfront area.
  • D. Higashi-ku
    Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
  • E. Taihaku-ku
    Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9e11c4188190a3ae8fd0cbd8c2c0 completed March 8, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda3e679a881908f91a36675037d1a completed March 20, 2026, 7:45 p.m.
Created at: March 8, 2026, 3 p.m.