Triple

T23219876
Position Surface form Disambiguated ID Type / Status
Subject Alix Madigan E580856 entity
Predicate notableWork P4 FINISHED
Object Clean 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: Clean | Statement: [Alix Madigan, notableWork, Clean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clean
Context triple: [Alix Madigan, notableWork, Clean]
  • A. Clean chosen
    Clean is a 2004 drama film by Olivier Assayas that follows a woman’s struggle with addiction and her attempt to rebuild her life and reconnect with her son.
  • B. Clean
    "Clean" is a reflective, emotionally resonant ballad by Taylor Swift that closes her 2014 album *1989*, symbolizing recovery and emotional renewal after heartbreak.
  • C. Clean
    "Clean" is a popular dancehall track by Jamaican artist Popcaan, known for its catchy hook and celebration of style and success.
  • D. Clean, Clean
    "Clean, Clean" is a lesser-known song by the British new wave band The Buggles, featured on their 1980 debut album "The Age of Plastic."
  • E. Limpio
    Limpio is a city in Paraguay located within the Central Department, known as part of the metropolitan area surrounding the capital, Asunción.
  • 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.