Triple

T19940642
Position Surface form Disambiguated ID Type / Status
Subject Κλάρος E479297 entity
Predicate nearModernSettlement P33888 FINISHED
Object Ahmetbeyli 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: Ahmetbeyli | Statement: [Κλάρος, nearModernSettlement, Ahmetbeyli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ahmetbeyli
Context triple: [Κλάρος, nearModernSettlement, Ahmetbeyli]
  • A. Ahmetbeyli chosen
    Ahmetbeyli is a coastal neighborhood and historical area in western Turkey known for its beaches and proximity to ancient ruins.
  • B. Bekir
    Bekir is a common Turkish male given name of Arabic origin, often associated with early Islamic history and frequently borne by notable figures in Turkey.
  • C. Bamsi Beyrek
    Bamsi Beyrek is a legendary hero of the Oghuz Turkic epic tradition, celebrated for his bravery, loyalty, and romantic exploits in the Book of Dede Korkut.
  • D. Şahin Bey
    Şahin Bey was an Ottoman military officer and national hero known for leading resistance against French forces during the Turkish War of Independence, particularly in the defense of Gaziantep.
  • E. Celal
    Celal is a central character in Orhan Pamuk’s novel "The Black Book," around whom much of the story’s mystery and identity exploration revolves.
  • 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_69d8e522a17c819095165d4d24939fd8 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a1a8df4819094e84855465df6c0 completed April 20, 2026, 4:53 p.m.
Created at: April 10, 2026, 1:53 p.m.