Triple

T9489207
Position Surface form Disambiguated ID Type / Status
Subject Terry Rossio E228841 entity
Predicate familyName P18 FINISHED
Object Rossio E460963 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: Rossio | Statement: [Terry Rossio, familyName, Rossio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rossio
Context triple: [Terry Rossio, familyName, Rossio]
  • A. Rossio chosen
    Rossio is a central Lisbon square and major transport hub known for its historic architecture, lively atmosphere, and role as a key meeting point in the city.
  • B. Renaico
    Renaico is a small town and commune in southern Chile’s Araucanía Region, known for its agricultural activities and location near the Vergara River.
  • C. Glorioso
    Glorioso is the traditional nickname of Brazilian football club Botafogo de Futebol e Regatas, reflecting its proud and storied history.
  • D. Franconero
    Franconero is the birth surname of American pop singer Connie Francis, one of the most successful female vocalists of the late 1950s and early 1960s.
  • E. Ferrera
    Ferrera is a Spanish-origin surname most prominently associated with American actress and producer America Ferrera.
  • 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_69ca847424f081908180305555139f7a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd80c5a05c8190b97d34f010e60ca1 completed April 1, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d202b748190b78e4e972b1ce08d completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:55 p.m.