Triple

T9160830
Position Surface form Disambiguated ID Type / Status
Subject Rebecca Lobo E219816 entity
Predicate familyName P18 FINISHED
Object Lobo E177678 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: Lobo | Statement: [Rebecca Lobo, familyName, Lobo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lobo
Context triple: [Rebecca Lobo, familyName, Lobo]
  • A. Lobo chosen
    Lobo is a surname most prominently associated with Rebecca Lobo, a former American professional basketball player and Hall of Famer.
  • B. Lobo
    Lobo is a coastal municipality in the province of Batangas in the Philippines, known for its beaches, dive sites, and marine biodiversity.
  • C. Loup
    The Loup is a river in southeastern France that flows through the Alpes-Maritimes department, known for its scenic gorges and popular outdoor recreation areas.
  • D. Lobos
    Lobos is the commonly used nickname for the Mexican football club Lobos BUAP, historically associated with the Benemérita Universidad Autónoma de Puebla.
  • E. Lobos
    Lobos is a small cay located off the coast of Fajardo, Puerto Rico, known for its clear waters and marine life.
  • 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_69ca83e3633c81908688a9fa2306ba99 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccaa2ac0508190b2f5c801c2c26d66 completed April 1, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0547073cc8190999fe640c7ccd373 completed April 3, 2026, 11:59 p.m.
Created at: March 30, 2026, 7:21 p.m.