Triple

T21288020
Position Surface form Disambiguated ID Type / Status
Subject Khamsa of Nizami E524712 entity
Predicate hasPart P35 FINISHED
Object Haft Paykar 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: Haft Paykar | Statement: [Khamsa of Nizami, hasPart, Haft Paykar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haft Paykar
Context triple: [Khamsa of Nizami, hasPart, Haft Paykar]
  • A. Haft Paykar chosen
    Haft Paykar is a 12th-century romantic and allegorical epic poem by Nizami Ganjavi, renowned for its intricate narrative structure and rich symbolism centered on the Sasanian king Bahram Gur.
  • B. Shahid Haghani
    Shahid Haghani was an Iranian figure commemorated as a martyr, after whom the Shahid Haghani Metro Station in Tehran is named.
  • C. Mirza Ghasemi
    Mirza Ghasemi is a popular smoky eggplant and tomato dish from northern Iran, especially associated with the cuisine of Gilan Province by the Caspian Sea.
  • D. Ramazan Bashardost
    Ramazan Bashardost is an Afghan politician and former planning minister known for his anti-corruption stance and populist, reformist campaigns for the presidency.
  • E. Mohammad Reza Isfahani
    Mohammad Reza Isfahani was a prominent Safavid-era Iranian architect best known for designing masterpieces of Isfahan’s royal square, including the celebrated Sheikh Lotfollah Mosque.
  • 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d7c57c8190bc4180ea590a62d4 completed April 21, 2026, 8:35 a.m.
Created at: April 16, 2026, 4:03 p.m.