Triple

T2914693
Position Surface form Disambiguated ID Type / Status
Subject I'm Every Woman E63772 entity
Predicate producer P490 FINISHED
Object Arif Mardin E247090 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: Arif Mardin | Statement: [I'm Every Woman, producer, Arif Mardin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arif Mardin
Context triple: [I'm Every Woman, producer, Arif Mardin]
  • A. Arif Mardin chosen
    Arif Mardin was a renowned Turkish-American record producer and arranger known for his influential work across pop, rock, and soul with artists such as Aretha Franklin, the Bee Gees, and Norah Jones.
  • B. Neal Hefti
    Neal Hefti was an American jazz trumpeter, composer, and arranger best known for his big band work and iconic television and film scores, including the theme for the 1960s Batman series.
  • C. Jaafar Tukan
    Jaafar Tukan was a prominent Palestinian architect known for designing significant modern public and cultural buildings across the Arab world.
  • D. Aftab Iqbal
    Aftab Iqbal was the son of the renowned philosopher-poet Allama Muhammad Iqbal and a Pakistani academic and literary figure in his own right.
  • E. Rehman Nizar Ali
    Rehman Nizar Ali is a film editor known for his work on the experimental romantic drama "Song to Song."
  • 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_69ab4c44ab448190b9411324e8a1fc1d completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe0edb1ac81908b22ef60abb4a4df completed March 7, 2026, 8:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69b056249b5c8190b388088bf047616f completed March 10, 2026, 5:34 p.m.
Created at: March 6, 2026, 10:11 p.m.