Triple

T19793084
Position Surface form Disambiguated ID Type / Status
Subject Matsuzakaya Nagoya E475467 entity
Predicate operator P179 FINISHED
Object Matsuzakaya NE NERFINISHED

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: Matsuzakaya | Statement: [Matsuzakaya Nagoya, operator, Matsuzakaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matsuzakaya
Context triple: [Matsuzakaya Nagoya, operator, Matsuzakaya]
  • A. Matsuzakaya Nagoya chosen
    Matsuzakaya Nagoya is a major flagship department store in central Nagoya, Japan, known for its long history, extensive shopping facilities, and role as a key commercial hub in the Sakae district.
  • B. Mizumoto
    Mizumoto is a neighborhood in Tokyo’s Katsushika ward, known for its large riverside Mizumoto Park and relatively green, residential environment.
  • C. Nissho
    Nissho was a prominent disciple of the Japanese Buddhist monk Nichiren who helped propagate and systematize Nichiren Buddhism.
  • D. Michishio
    Michishio was a Japanese Navy destroyer that served in World War II and was sunk during the Battle of Surigao Strait in 1944.
  • E. Mibuchi
    Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653c4a8a88190afc2f2cd1ebbbe1e completed April 20, 2026, 4:26 p.m.
Created at: April 10, 2026, 1:49 p.m.