Triple

T12548189
Position Surface form Disambiguated ID Type / Status
Subject Fujiko F. Fujio Museum E300026 entity
Predicate owner P347 FINISHED
Object Kawasaki City E624625 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: Kawasaki City | Statement: [Fujiko F. Fujio Museum, owner, Kawasaki City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kawasaki City
Context triple: [Fujiko F. Fujio Museum, owner, Kawasaki City]
  • A. Kawasaki City chosen
    Kawasaki City is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along Tokyo Bay.
  • B. Osaki City
    Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
  • C. Miyazaki City
    Miyazaki City is a coastal city in southeastern Kyushu, Japan, known for its mild climate, beaches, and role as an administrative and cultural center of the region.
  • D. Kitakyushu
    Kitakyushu is a major industrial and port city located in Fukuoka Prefecture on Japan’s Kyushu island.
  • E. Yokkaichi
    Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
  • 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_69d6ada707008190aaec1238117c9379 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d95481ba28819099f7cd2de02e8837 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce5b2b988190892e14620fb87366 completed May 3, 2026, 10:38 p.m.
Created at: April 8, 2026, 9:58 p.m.