Triple

T4544358
Position Surface form Disambiguated ID Type / Status
Subject Big Egg E110011 entity
Predicate locatedInWard P40 FINISHED
Object Bunkyo E469604 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: Bunkyo | Statement: [Big Egg, locatedInWard, Bunkyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bunkyo
Context triple: [Big Egg, locatedInWard, Bunkyo]
  • A. Bunkyō chosen
    Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
  • B. Chiyoda
    Chiyoda is a central special ward of Tokyo that serves as Japan’s political and administrative hub, housing the Imperial Palace, the National Diet, and many government institutions.
  • C. Chiyoda
    Chiyoda was a Japanese light aircraft carrier of the Imperial Japanese Navy that served in World War II and was sunk during the Battle off Cape Engaño in 1944.
  • D. Kōtō
    Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
  • E. Toshima
    Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
  • 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_69bd4412524c8190be5bcc9ddee91848 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57d517e881909c3d23ed4453b0a7 completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfe31f64c88190b093e2bd65ae731b completed March 22, 2026, 12:39 p.m.
Created at: March 20, 2026, 1:05 p.m.