Triple

T9943586
Position Surface form Disambiguated ID Type / Status
Subject Komaba E194143 entity
Predicate locatedIn P40 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: [Komaba, locatedIn, Meguro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meguro
Context triple: [Komaba, locatedIn, 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. 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.
  • D. Minami-Osawa
    Minami-Osawa is a suburban district in Tama, Tokyo, known for its large shopping centers, university campuses, and role as a key residential and commercial hub within Tama New Town.
  • E. Setagaya
    Setagaya is a large residential ward in western Tokyo, Japan, known for its suburban neighborhoods, parks, and role as a commuter area for central Tokyo.
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb613fbb48190b82a06987310cc96 completed April 2, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6035cf86081909603cec9aa5bd9d6 completed April 20, 2026, 10:43 a.m.
Created at: March 30, 2026, 8:45 p.m.