Triple

T8536719
Position Surface form Disambiguated ID Type / Status
Subject Elle UK E202094 entity
Predicate parentPublication P5593 FINISHED
Object Elle E39387 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: Elle | Statement: [Elle UK, parentPublication, Elle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elle
Context triple: [Elle UK, parentPublication, 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 (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.
  • D. Amour
    *Amour* is a poetry collection by French Symbolist poet Paul Verlaine, reflecting his characteristic musicality, emotional nuance, and exploration of love and spirituality.
  • E. Amour
    Amour is a critically acclaimed 2012 French-language drama film directed by Michael Haneke that portrays an elderly couple’s struggle with illness and the limits of love and dignity.
  • 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_69ca832355b08190b8b6a4ab4a4a3554 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6a3f024819095d560a205ff1c75 completed March 31, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d8c666881908785079f059f88c8 completed April 2, 2026, 1:22 p.m.
Created at: March 30, 2026, 6:18 p.m.