Triple

T15900819
Position Surface form Disambiguated ID Type / Status
Subject The Waitresses E385582 entity
Predicate basedIn P40 FINISHED
Object Akron, Ohio E1125626 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: Akron, Ohio | Statement: [The Waitresses, basedIn, Akron, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akron, Ohio
Context triple: [The Waitresses, basedIn, Akron, Ohio]
  • A. Akron
    Akron is an industrial city in northeastern Ohio known historically for its rubber and tire manufacturing industry.
  • B. Akron, Michigan
    Akron, Michigan is a small rural village located in Tuscola County in the Thumb region of the U.S. state of Michigan.
  • C. Hamilton, Ohio
    Hamilton, Ohio is a historic industrial city in southwestern Ohio that serves as the county seat of Butler County and is part of the greater Cincinnati–Miami Valley region.
  • D. Akron, Ohio, United States chosen
    Akron is a mid-sized industrial city in northeastern Ohio, United States, historically known for its rubber and tire manufacturing industry.
  • E. Cleveland
    Cleveland is a small city in northeastern Georgia known as a gateway to the Appalachian Mountains and nearby gold-mining and outdoor recreation areas.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563cd2f081909404d724ecc8785a completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00179d63688190bda2758ed4b4e4df completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 4:51 a.m.