Triple

T1743144
Position Surface form Disambiguated ID Type / Status
Subject Joe Zee E38275 entity
Predicate employer P7 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: [Joe Zee, employer, Elle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elle
Context triple: [Joe Zee, employer, 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. Sils Maria
    Sils Maria is a Swiss Alpine village in the Engadin valley, best known as a summer retreat of philosopher Friedrich Nietzsche and a source of inspiration for some of his major works.
  • D. Gigi
    Gigi was the affectionate nickname of Gianna Bryant, the late daughter of NBA legend Kobe Bryant who was known for her own promising basketball talent.
  • E. Gigi
    Gigi is a 1958 American musical romantic comedy film, directed by Vincente Minnelli, that won multiple Academy Awards and is celebrated for its lavish production and memorable score.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c836d48190bd44ea24977aba2d completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0dbc7c081909d637c5a482389ef completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.