Triple

T11599943
Position Surface form Disambiguated ID Type / Status
Subject Samar Mubarakmand E275101 entity
Predicate name P16 FINISHED
Object Samar Mubarakmand E275101 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: Samar Mubarakmand | Statement: [Samar Mubarakmand, name, Samar Mubarakmand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samar Mubarakmand
Context triple: [Samar Mubarakmand, name, Samar Mubarakmand]
  • A. Samar Mubarakmand chosen
    Samar Mubarakmand is a Pakistani nuclear physicist and defense scientist renowned for his key leadership role in developing Pakistan’s nuclear weapons program.
  • B. Mudar Badran
    Mudar Badran was a prominent Jordanian politician and statesman who served multiple terms in high government office during the late 20th century.
  • C. Nadia Dajani
    Nadia Dajani is an American actress known for her work in television, film, and theater, including prominent roles in 1990s sitcoms and various independent films.
  • D. Kinan Azmeh
    Kinan Azmeh is a Syrian clarinetist and composer known for blending classical, jazz, and Middle Eastern musical traditions in his performances and compositions.
  • E. Ziama Mansouriah
    Ziama Mansouriah is a coastal town and commune in northeastern Algeria known for its Mediterranean shoreline and location within Jijel Province.
  • 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_69d6aae6b14c81908dc5a74bad7591f9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8954c3c248190bcccd4c7ff667b3a completed April 10, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69e8a7dd83d48190b281a6fcfc3e4087 completed April 22, 2026, 10:50 a.m.
Created at: April 8, 2026, 9:38 p.m.