Triple

T11744396
Position Surface form Disambiguated ID Type / Status
Subject Tokyo 23 wards E279238 entity
Predicate containsAdministrativeDivision P747 FINISHED
Object Meguro E251913 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: Meguro | Statement: [Tokyo 23 wards, containsAdministrativeDivision, Meguro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meguro
Context triple: [Tokyo 23 wards, containsAdministrativeDivision, Meguro]
  • A. Shinagawa
    Shinagawa is a major commercial and transportation hub in Tokyo, Japan, known for its busy railway station, business districts, and waterfront developments.
  • B. Meguro Ward chosen
    Meguro Ward is a residential and commercial district in southwest Tokyo known for its urban neighborhoods, cultural sites, and convenient rail access to central Tokyo.
  • C. Nakameguro
    Nakameguro is a trendy Tokyo neighborhood known for its cherry tree–lined Meguro River, stylish cafes, boutiques, and vibrant nightlife.
  • D. Itabashi
    Itabashi is a special ward in northern Tokyo, Japan, known as a primarily residential area with a mix of traditional neighborhoods and modern urban infrastructure.
  • E. Nishi-Ogikubo
    Nishi-Ogikubo is a Tokyo neighborhood known for its laid-back residential atmosphere, vintage and antique shops, and small independent cafes and bars.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4f2a38c8190a682d8dae1ab9415 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2ce12e78819080b3fe19c57ef3ef completed May 9, 2026, 12:47 p.m.
Created at: April 8, 2026, 9:41 p.m.