Triple

T21945286
Position Surface form Disambiguated ID Type / Status
Subject Farah Naaz E541917 entity
Predicate name P16 FINISHED
Object Farah Naaz NE NERFINISHED

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: Farah Naaz | Statement: [Farah Naaz, name, Farah Naaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Farah Naaz
Context triple: [Farah Naaz, name, Farah Naaz]
  • A. Farah Naaz chosen
    Farah Naaz is an Indian film actress known for her prominent roles in Hindi cinema during the late 1980s and early 1990s.
  • B. Gauhar Ara Begum
    Gauhar Ara Begum was a Mughal princess, the daughter of Emperor Shah Jahan and his famed consort Mumtaz Mahal, and a member of the imperial family during the empire’s zenith in 17th-century India.
  • C. Shibani Khan
    Shibani Khan, also known as Muhammad Shaybani, was a prominent Uzbek ruler and military leader who founded the Shaybanid dynasty in Central Asia in the late 15th and early 16th centuries.
  • D. Rubaiya Sayeed
    Rubaiya Sayeed is an Indian doctor who became widely known after her high-profile 1989 kidnapping by militants in Jammu and Kashmir, an event that had major political repercussions in the region.
  • E. Nida Fazli
    Nida Fazli was a renowned Indian Urdu-Hindi poet and lyricist known for his poignant, humanistic verses and memorable film songs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47e2e5c81909a7f74ce3de50911 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1242688988190a7b8f033c49368de completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:56 p.m.