Triple

T16589025
Position Surface form Disambiguated ID Type / Status
Subject Naseeruddin Shah E403033 entity
Predicate notableWork P4 FINISHED
Object Sarfarosh E392741 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: Sarfarosh | Statement: [Naseeruddin Shah, notableWork, Sarfarosh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarfarosh
Context triple: [Naseeruddin Shah, notableWork, Sarfarosh]
  • A. Sarfarosh chosen
    Sarfarosh is a 1999 Indian Hindi-language action drama film acclaimed for its gritty portrayal of cross-border terrorism and for featuring Aamir Khan in a powerful lead role as an honest police officer.
  • B. Fida'i
    Fida'i is the national anthem of the State of Palestine, expressing Palestinian identity, struggle, and aspirations for freedom and self-determination.
  • C. Taymuri
    Taymuri are a sub-group of the Aimaq people, traditionally semi-nomadic pastoralists living mainly in western and central Afghanistan.
  • D. Qabiha
    Qabiha was a consort of the Abbasid caliph al-Mu'tamid, associated with the 9th-century Abbasid court.
  • E. Kaffal Shashi
    Kaffal Shashi was a prominent 10th-century Islamic scholar, jurist, and Sufi saint from Tashkent, revered as one of the earliest and most influential Muslim figures in Central Asia.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3599e79288190b6bcdb6fe4a2d1fa completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a007599dcd4819089bbd0569b3d9a12 completed May 10, 2026, 12:10 p.m.
Created at: April 10, 2026, 5:16 a.m.