Triple

T4655878
Position Surface form Disambiguated ID Type / Status
Subject School of Engineering Science E102406 entity
Predicate city P40 FINISHED
Object Toyonaka E24760 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: Toyonaka | Statement: [School of Engineering Science, city, Toyonaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyonaka
Context triple: [School of Engineering Science, city, Toyonaka]
  • A. Toyonaka chosen
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • B. Nishi-Tobecho
    Nishi-Tobecho is a notable neighborhood within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
  • C. 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.
  • D. Yanaka
    Yanaka is a traditional, temple-filled neighborhood in Tokyo known for its preserved old-town atmosphere, narrow lanes, and historic cemetery.
  • E. Kitano-cho
    Kitano-cho is a historic district in Kobe, Japan, known for its preserved Western-style residences built by foreign merchants in the late 19th and early 20th centuries.
  • 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63193a108190a7d9aec1d1d40cf8 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5187dfe008190ac60e042527e55b3 completed March 26, 2026, 11:29 a.m.
Created at: March 20, 2026, 1:14 p.m.