Triple

T9879018
Position Surface form Disambiguated ID Type / Status
Subject Independent Women Part I E240153 entity
Predicate writer P1360 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: [Independent Women Part I, writer, J.R. Rotem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: J.R. Rotem
Context triple: [Independent Women Part I, writer, 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. Nir Bergman
    Nir Bergman is an Israeli film and television director and screenwriter known for his influential work in character-driven dramas.
  • C. Paul Ben-Haim
    Paul Ben-Haim was a prominent German-born Israeli composer and conductor, known as a pioneer of Israeli art music who blended Western classical traditions with Middle Eastern and Jewish musical elements.
  • D. Lior Raz
    Lior Raz is an Israeli actor and screenwriter best known as the co-creator and star of the hit television series "Fauda."
  • E. Tom Erez
    Tom Erez is a researcher in machine learning and control, known for his work on deep reinforcement learning algorithms such as Deep Deterministic Policy Gradient (DDPG).
  • 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_69ca84e8a0788190b9061811d50fd554 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb4135c108190b3330e929509699d completed April 2, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e480ead08190992eb43ea3eac38b completed April 5, 2026, 4:26 a.m.
Created at: March 30, 2026, 8:37 p.m.