Triple

T21018028
Position Surface form Disambiguated ID Type / Status
Subject Isfahan school E517730 entity
Predicate notableArtist P601 FINISHED
Object Reza Abbasi 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: Reza Abbasi | Statement: [Isfahan school, notableArtist, Reza Abbasi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reza Abbasi
Context triple: [Isfahan school, notableArtist, Reza Abbasi]
  • A. Reza Abbasi chosen
    Reza Abbasi was a prominent Safavid-era Persian painter renowned for his elegant single-figure miniatures and influential role in the Isfahan school of art.
  • B. Reza Radmanesh
    Reza Radmanesh was an Iranian communist politician and prominent leader of the Tudeh Party of Iran, active in mid-20th-century leftist politics.
  • C. Reza Mirkarimi
    Reza Mirkarimi is an acclaimed Iranian film director and screenwriter known for his humanistic dramas and significant contributions to contemporary Iranian cinema.
  • D. Mehdi Hatamian
    Mehdi Hatamian is an electrical engineer and technologist recognized for his influential contributions to high-speed integrated circuits and signal processing, for which he has received major industry honors.
  • E. Shervin Alenabi
    Shervin Alenabi is an actor best known for his role in the espionage thriller television series "Tehran."
  • 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_69e0b50262b081909bc488937145eb73 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc5a27f08190b26828a6a7b59f7c completed April 21, 2026, 4:26 a.m.
Created at: April 16, 2026, 1:54 p.m.