Triple

T18112538
Position Surface form Disambiguated ID Type / Status
Subject Thomas E433515 entity
Predicate hasVariant P455 FINISHED
Object Tomé 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: Tomé | Statement: [Thomas, hasVariant, Tomé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tomé
Context triple: [Thomas, hasVariant, Tomé]
  • A. Tomé
    Tomé is a coastal commune and city in Chile’s Biobío Region, known for its textile industry, fishing activities, and beaches.
  • B. Tomé
    Tomé is a small unincorporated community in Valencia County, New Mexico, known historically as a Spanish colonial settlement along the Rio Grande.
  • C. Santo Tomás
    Santo Tomás is a town in the Cusco Region of Peru that serves as the administrative and commercial center of Chumbivilcas Province.
  • D. Santo Tomás
    Santo Tomás is a small settlement within Cuba’s Ciénaga de Zapata region, known for its proximity to extensive wetlands and rich biodiversity.
  • E. Santo Tomás
    Santo Tomás is a municipality in Nicaragua’s Chontales Department, known for its agricultural activities and small-town regional center role.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddd3422c81908396a21bd53f3e47 completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:28 a.m.