Triple

T10467572
Position Surface form Disambiguated ID Type / Status
Subject Prince of Persia: The Sands of Time E246835 entity
Predicate hasCharacter P2308 FINISHED
Object Nizam E850380 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: Nizam | Statement: [Prince of Persia: The Sands of Time, hasCharacter, Nizam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nizam
Context triple: [Prince of Persia: The Sands of Time, hasCharacter, Nizam]
  • A. Nizam
    Nizam was the hereditary title of the monarchs who ruled the princely state of Hyderabad in India, known for their immense wealth and semi-autonomous power under British rule.
  • B. Nabíl-i-Aʿzam
    Nabíl-i-Aʿzam was a prominent 19th-century Baháʼí historian and poet best known for chronicling the early history of the Bábí and Baháʼí Faiths.
  • C. Najm-ud-Daulah
    Najm-ud-Daulah was an 18th-century Nawab of Bengal who succeeded his father Mir Jafar under the dominance of the British East India Company.
  • D. Mirza Asadullah Baig Khan
    Mirza Asadullah Baig Khan, better known by his pen name Mirza Ghalib, was a preeminent 19th-century Urdu and Persian poet whose ghazals are considered masterpieces of South Asian literature.
  • E. Raza Murad chosen
    Raza Murad is an Indian character actor known for his deep voice and frequent portrayals of villains and authoritative figures in Hindi cinema.
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5092e3230819098ab444f73c9bd40 completed April 7, 2026, 1:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d89ff1cd948190a1ef331fb810bf26 completed April 10, 2026, 7 a.m.
Created at: April 6, 2026, 12:20 p.m.