Triple

T21293126
Position Surface form Disambiguated ID Type / Status
Subject Ezzatolah Entezami E524846 entity
Predicate notableWork P4 FINISHED
Object Hezar Dastan — NE NERFINISHED

How this triple was built (3 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: Hezar Dastan | Statement: [Ezzatolah Entezami, notableWork, Hezar Dastan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hezar Dastan
Context triple: [Ezzatolah Entezami, notableWork, Hezar Dastan]
  • A. Shams of Tabriz
    Shams of Tabriz was a 13th-century Persian mystic and wandering dervish best known as the spiritual mentor and transformative influence of the poet Rumi.
  • B. Persian Nights
    Persian Nights is a novel by American author Diane Johnson that blends psychological insight with cultural observation in a story set against the backdrop of the Middle East.
  • C. Rostam-e Dastan
    Rostam-e Dastan is the legendary Persian hero of the Shahnameh, famed for his superhuman strength, loyalty, and epic exploits in Iranian mythology.
  • D. Das Märchen der 672. Nacht
    Das Märchen der 672. Nacht is a symbolist novella by Austrian writer Hugo von Hofmannsthal that explores themes of decadence, fate, and psychological disintegration in a dreamlike, oriental setting.
  • E. Song of Scheherazade
    "Song of Scheherazade" is a 1947 romantic musical film inspired by the tales of Scheherazade, featuring Yvonne De Carlo in a prominent role.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hezar Dastan
Target entity description: Hezar Dastan is a renowned Iranian television series, celebrated as a classic of Persian-language drama and noted for its rich storytelling and memorable characters.
  • A. Shams of Tabriz
    Shams of Tabriz was a 13th-century Persian mystic and wandering dervish best known as the spiritual mentor and transformative influence of the poet Rumi.
  • B. Persian Nights
    Persian Nights is a novel by American author Diane Johnson that blends psychological insight with cultural observation in a story set against the backdrop of the Middle East.
  • C. Rostam-e Dastan
    Rostam-e Dastan is the legendary Persian hero of the Shahnameh, famed for his superhuman strength, loyalty, and epic exploits in Iranian mythology.
  • D. Das Märchen der 672. Nacht
    Das Märchen der 672. Nacht is a symbolist novella by Austrian writer Hugo von Hofmannsthal that explores themes of decadence, fate, and psychological disintegration in a dreamlike, oriental setting.
  • E. Song of Scheherazade
    "Song of Scheherazade" is a 1947 romantic musical film inspired by the tales of Scheherazade, featuring Yvonne De Carlo in a prominent role.
  • F. None of above. chosen

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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73855e5d08190aed5e285247b4e23 completed April 21, 2026, 8:41 a.m.
Created at: April 16, 2026, 4:04 p.m.