Triple

T17973185
Position Surface form Disambiguated ID Type / Status
Subject Alexa Demie E449397 entity
Predicate hasGivenInterviewTo P40000 FINISHED
Object Elle NE NERFINISHED

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: Elle | Statement: [Alexa Demie, hasGivenInterviewTo, Elle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elle
Context triple: [Alexa Demie, hasGivenInterviewTo, Elle]
  • A. Elle chosen
    Elle is a globally recognized fashion and lifestyle magazine known for its coverage of style, beauty, culture, and celebrity features.
  • B. Elle
    Elle is the solitary female protagonist of Francis Poulenc’s one-act opera *La voix humaine*, whose intense telephone monologue lays bare her emotional collapse during a breakup.
  • C. Elle
    Elle is the codename of Elle Driver, a deadly one-eyed assassin from Quentin Tarantino’s Kill Bill films.
  • D. Elle (2016 film)
    Elle is a 2016 French psychological thriller film directed by Paul Verhoeven, starring Isabelle Huppert as a successful businesswoman who seeks to track down the man who assaulted her.
  • E. Amour
    *Amour* is a poetry collection by French Symbolist poet Paul Verlaine, reflecting his characteristic musicality, emotional nuance, and exploration of love and spirituality.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b1fca04481908f0dd875953fd82f completed April 19, 2026, 10:44 a.m.
Created at: April 10, 2026, 10:22 a.m.