Triple

T23265948
Position Surface form Disambiguated ID Type / Status
Subject Tevfik Esenç E588147 entity
Predicate givenName P17 FINISHED
Object Tevfik 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: Tevfik | Statement: [Tevfik Esenç, givenName, Tevfik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tevfik
Context triple: [Tevfik Esenç, givenName, Tevfik]
  • A. Tevfik chosen
    Tevfik is a central fictional character in the classic Turkish novel "Sinekli Bakkal" by Halide Edib Adıvar.
  • B. Mehmet Reşit
    Mehmet Reşit was an Ottoman politician and physician associated with the Young Turk movement and the Committee of Union and Progress.
  • C. Necati Bey
    Necati Bey was a prominent Turkish educator and intellectual whose legacy in advancing teacher training and education in Turkey is commemorated by institutions bearing his name.
  • D. Mahmut Celâl
    Mahmut Celâl is the given name of Celâl Bayar, a prominent Turkish statesman who served as the third President of Turkey.
  • E. Mehmet Tevfik
    Mehmet Tevfik, better known by his pen name Tevfik Fikret, was a prominent late Ottoman-era Turkish poet and a leading figure of modern Turkish literature.
  • 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_69e25d148adc819088efbf42672604e9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f194cc3b908190aaefd036aa2b52b5 completed April 29, 2026, 5:19 a.m.
Created at: April 17, 2026, 4:35 p.m.