Triple

T9226482
Position Surface form Disambiguated ID Type / Status
Subject Isabel Moniz E221694 entity
Predicate givenName P17 FINISHED
Object Isabel E114378 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: Isabel | Statement: [Isabel Moniz, givenName, Isabel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isabel
Context triple: [Isabel Moniz, givenName, Isabel]
  • A. Isabel chosen
    Isabel is a feminine given name of Spanish origin, widely used in Spanish- and Portuguese-speaking countries and borne by numerous notable historical and contemporary figures.
  • B. Isabel
    Isabel is a Spanish historical drama television series centered on the life and reign of Queen Isabella I of Castile.
  • C. Isabelle
    Isabelle is a popular character from the Animal Crossing series who also appears as a playable racer in Mario Kart 8.
  • D. Isabel Rivers
    Isabel Rivers is a central character in the adventure novel "Beau Geste," closely connected to the Geste brothers and their dramatic exploits.
  • E. Isabella
    Isabella is a virtuous and resourceful young noblewoman in Horace Walpole’s Gothic novel "The Castle of Otranto," whose peril and resistance drive much of the story’s suspense and drama.
  • 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_69ca83ec8db08190a9110df8232885d2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda9ecef48190b8aa0e316d07cec7 completed April 1, 2026, 8:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69d066521f288190a54b1199284db7a4 completed April 4, 2026, 1:16 a.m.
Created at: March 30, 2026, 7:28 p.m.