Triple

T11830654
Position Surface form Disambiguated ID Type / Status
Subject Isabelle Azaire E281380 entity
Predicate givenName P17 FINISHED
Object Isabelle
Isabelle is a feminine given name of French origin, commonly used in many countries and cultures.
 E952172 NE FINISHED

How this triple was built (4 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 Azaire, givenName, Isabelle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Isabelle
Context triple: [Isabelle Azaire, 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. 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.
  • D. Isabel
    Isabel is a Spanish historical drama television series centered on the life and reign of Queen Isabella I of Castile.
  • E. Isabella
    Isabella was a Spanish Habsburg archduchess who governed the Spanish Netherlands in the late 16th and early 17th centuries.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Isabelle
Triple: [Isabelle Azaire, givenName, Isabelle]
Generated description
Isabelle is a feminine given name of French origin, commonly used in many countries and cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Isabelle
Target entity description: Isabelle is a feminine given name of French origin, commonly used in many countries and cultures.
  • 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. 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.
  • D. Isabel
    Isabel is a Spanish historical drama television series centered on the life and reign of Queen Isabella I of Castile.
  • E. Isabella
    Isabella was a Spanish Habsburg archduchess who governed the Spanish Netherlands in the late 16th and early 17th centuries.
  • F. None of above. chosen

Provenance (5 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a62b75dc8190b27d24e46a262a11 completed April 10, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69f2812007dc81908e56fd47b2a94836 completed April 29, 2026, 10:07 p.m.
NEDg Description generation batch_69f40b2d0a388190a11a0e2d806e310b completed May 1, 2026, 2:08 a.m.
NED2 Entity disambiguation (via description) batch_69f40deb4eec8190a8fe1aa59b1514e6 completed May 1, 2026, 2:20 a.m.
Created at: April 8, 2026, 9:43 p.m.