Triple

T1616328
Position Surface form Disambiguated ID Type / Status
Subject Würzburg E34725 entity
Predicate hasTwinTown P919 FINISHED
Object Rochester, New York E22338 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: Rochester, New York | Statement: [Würzburg, hasTwinTown, Rochester, New York]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rochester, New York
Context triple: [Würzburg, hasTwinTown, Rochester, New York]
  • A. Rochester
    Rochester is a historic cathedral city and former market town in Kent, England, known for its Norman castle, Romanesque cathedral, and strong associations with the novelist Charles Dickens.
  • B. Rochester
    Rochester is a small borough in western Pennsylvania situated along the Ohio River in Beaver County.
  • C. Rochester chosen
    Rochester is a major city in western New York State known historically for its role in industry, photography, and social reform movements.
  • D. Rochester
    Rochester is a small historic town in southeastern Massachusetts known for its rural character and New England charm.
  • E. Rochester
    Rochester is a major city in southeastern Minnesota known for being the home of the world-renowned Mayo Clinic.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9099049e0819099763ecb09fb4f57 completed March 5, 2026, 4:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f6a15f081909b83d24a7b470eba completed March 9, 2026, 7:28 p.m.
Created at: March 4, 2026, 7:28 p.m.