Triple

T3970905
Position Surface form Disambiguated ID Type / Status
Subject Rouben Mamoulian E92331 entity
Predicate givenName P17 FINISHED
Object Rouben E92331 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: Rouben | Statement: [Rouben Mamoulian, givenName, Rouben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rouben
Context triple: [Rouben Mamoulian, givenName, Rouben]
  • A. Rouben chosen
    Rouben is a masculine given name most notably borne by Armenian-American film and theatre director Rouben Mamoulian.
  • B. Simon Vratsian
    Simon Vratsian was an Armenian statesman, revolutionary, and leader of the Armenian Revolutionary Federation who served as the final head of government of independent Armenia before Sovietization.
  • C. Calouste
    Calouste is an Armenian-British businessman and philanthropist best known for his pivotal role in the early oil industry and for founding the Calouste Gulbenkian Foundation.
  • D. Bash Norashen
    Bash Norashen was a historical town that served as the administrative center of the Sharur-Daralayaz uezd in the Russian Empire’s Erivan Governorate.
  • E. Zareh Nalbandian
    Zareh Nalbandian is an Australian film producer and co-founder of the visual effects and animation studio Animal Logic, known for work on major feature films.
  • 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_69aed96624188190ac8c45bb57ab72b5 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef995d27881908b24a5b2ef57455f completed March 9, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5400b75d081909b8e4840b15d19f1 completed March 14, 2026, 11:01 a.m.
Created at: March 9, 2026, 3:32 p.m.