Triple

T3563539
Position Surface form Disambiguated ID Type / Status
Subject Tha Blue Carpet Treatment E75391 entity
Predicate producer P490 FINISHED
Object J.R. Rotem E344626 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: J.R. Rotem | Statement: [Tha Blue Carpet Treatment, producer, J.R. Rotem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: J.R. Rotem
Context triple: [Tha Blue Carpet Treatment, producer, J.R. Rotem]
  • A. J.R. Rotem chosen
    J.R. Rotem is a South African-born American record producer and songwriter known for crafting pop and hip-hop hits for artists such as Rihanna, Jason Derulo, and Sean Kingston.
  • B. Amir Shinar
    Amir Shinar is an Israeli entrepreneur and software engineer best known as one of the co-founders of the GPS navigation and traffic app Waze.
  • C. Avi Lerner
    Avi Lerner is an Israeli-American film producer and founder of Millennium Films, known for financing and producing numerous action movies and franchises.
  • D. Ilan Eshkeri
    Ilan Eshkeri is a British composer known for his orchestral film scores and collaborations on movies, television, and video games.
  • E. Yoni Brenner
    Yoni Brenner is a screenwriter and humorist known for his work on animated films, including contributing to the screenplay of "Rio 2."
  • 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_69ad85d512708190829c8b2d3a2ccfb8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0a60e6c8190a3c3ddae5b6ded54 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b402e8628c81909913974602782b7a completed March 13, 2026, 12:28 p.m.
Created at: March 8, 2026, 3:21 p.m.