Triple

T3368386
Position Surface form Disambiguated ID Type / Status
Subject Picenum E70891 entity
Predicate borders P224 FINISHED
Object Sabina E203655 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: Sabina | Statement: [Picenum, borders, Sabina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabina
Context triple: [Picenum, borders, Sabina]
  • A. Sabina
    Sabina is a central character in Thornton Wilder’s play "The Skin of Our Teeth," serving as both a maid and a self-aware, often comedic commentator who breaks the fourth wall to reflect on the absurdities of human existence.
  • B. Sabina chosen
    Sabina is a historical region of central Italy, traditionally inhabited by the Sabines and known for its rugged landscape and proximity to ancient Rome.
  • C. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • D. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • E. Sabine
    Sabine is a surname most notably associated with Wallace Clement Sabine, the American physicist who founded the field of architectural acoustics.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb28a813c81909d1c71fe577e6681 completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b334396f588190add5c0c27949650c completed March 12, 2026, 9:46 p.m.
Created at: March 8, 2026, 3:13 p.m.