Triple

T14637748
Position Surface form Disambiguated ID Type / Status
Subject 99 Homes E343649 entity
Predicate writer P1360 FINISHED
Object Amir Naderi E849576 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: Amir Naderi | Statement: [99 Homes, writer, Amir Naderi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amir Naderi
Context triple: [99 Homes, writer, Amir Naderi]
  • A. Amir Naderi chosen
    Amir Naderi is an acclaimed Iranian filmmaker and screenwriter known for influential works in Iranian New Wave cinema and later international films.
  • B. Amir Esmailian
    Amir Esmailian is a Canadian music executive and talent manager best known for co-founding XO and helping develop the career of The Weeknd.
  • C. Hossein Amini
    Hossein Amini is an Iranian-British screenwriter and director known for his work on films such as "Drive," "The Wings of the Dove," and various literary adaptations.
  • D. Behzad Farahani
    Behzad Farahani is an Iranian actor and playwright known for his significant contributions to Iranian theater and cinema.
  • E. 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.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4aca6448190adf1042dfbfef716 completed April 14, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cdc54a881909d9ea43c26b9d5ef completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:26 a.m.