Triple

T15094270
Position Surface form Disambiguated ID Type / Status
Subject Isabelle Rimbaud E360496 entity
Predicate givenName P17 FINISHED
Object Isabelle E952172 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: Isabelle | Statement: [Isabelle Rimbaud, givenName, Isabelle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isabelle
Context triple: [Isabelle Rimbaud, givenName, Isabelle]
  • A. Isabelle
    Isabelle is a popular character from the Animal Crossing series who also appears as a playable racer in Mario Kart 8.
  • B. Isabelle
    Isabelle is a prominent interactive theorem prover and proof assistant widely used in formal verification and mathematical logic research.
  • C. Isabelle chosen
    Isabelle is a feminine given name of French origin, commonly used in many countries and cultures.
  • D. Isabel
    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.
  • E. Isabel
    Isabel is a Spanish historical drama television series centered on the life and reign of Queen Isabella I of Castile.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0054571a48190a57055c0d6e90f82 completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69feb7e47b20819084145008474f47b7 completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 3:04 a.m.