Triple

T23219884
Position Surface form Disambiguated ID Type / Status
Subject Alix Madigan E580856 entity
Predicate notableWork P4 FINISHED
Object Laggies (2014 film) 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: Laggies (2014 film) | Statement: [Alix Madigan, notableWork, Laggies (2014 film)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laggies (2014 film)
Context triple: [Alix Madigan, notableWork, Laggies (2014 film)]
  • A. Laggies chosen
    Laggies is a 2014 American coming-of-age romantic comedy film directed by Lynn Shelton and starring Keira Knightley, Chloë Grace Moretz, and Sam Rockwell.
  • B. Lagg
    Lagg is a village on the Isle of Arran in Scotland, known for its coastal setting and association with whisky production.
  • C. Lagting
    Lagting was one of the two former chambers of the Norwegian Parliament, historically functioning as its upper house before the legislature became unicameral.
  • D. Lagut
    Lagut is an island located within the Rab archipelago.
  • E. Lag Jaa Gale
    "Lag Jaa Gale" is a classic Hindi film song, renowned for its haunting melody and emotional depth, sung by legendary playback singer Lata Mangeshkar.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1916870148190853874e6cf26bbc7 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.