Triple

T18593540
Position Surface form Disambiguated ID Type / Status
Subject Ahmed Ağaoğlu E454430 entity
Predicate alsoKnownAs P39 FINISHED
Object Ahmet Ağaoğlu 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: Ahmet Ağaoğlu | Statement: [Ahmed Ağaoğlu, alsoKnownAs, Ahmet Ağaoğlu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ahmet Ağaoğlu
Context triple: [Ahmed Ağaoğlu, alsoKnownAs, Ahmet Ağaoğlu]
  • A. Ahmed Ağaoğlu chosen
    Ahmed Ağaoğlu was a prominent late Ottoman and early Republican Turkish-Azerbaijani intellectual, journalist, and politician known for his advocacy of modernization, nationalism, and liberal reforms.
  • B. Ahmet Üzümcü
    Ahmet Üzümcü is a Turkish diplomat best known for leading the Organisation for the Prohibition of Chemical Weapons during its Nobel Peace Prize–winning efforts to eliminate chemical weapons.
  • C. Mehmet Çevik
    Mehmet Çevik is a Turkish actor best known for his roles in popular historical television dramas.
  • D. Murat Birsel
    Murat Birsel is a Turkish media professional best known as the husband of prominent screenwriter, actress, and columnist Gülse Birsel.
  • E. Feridun Zaimoglu
    Feridun Zaimoglu is a German-Turkish author and artist known for his influential novels, essays, and plays that explore migration, identity, and multicultural life in Germany.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e545b7ce3881908302ee27a2cf80d6 completed April 19, 2026, 9:14 p.m.
Created at: April 10, 2026, 11:44 a.m.