Triple

T6745949
Position Surface form Disambiguated ID Type / Status
Subject Şehzade Mehmed E154213 entity
Predicate associatedLocation P37 FINISHED
Object Manisa E332946 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: Manisa | Statement: [Şehzade Mehmed, associatedLocation, Manisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manisa
Context triple: [Şehzade Mehmed, associatedLocation, Manisa]
  • A. Manisa chosen
    Manisa is a historic city in western Turkey known for its agricultural production, especially grapes and olives, and its proximity to the Aegean coast.
  • B. Isparta
    Isparta is a city in southwestern Turkey known for its rose cultivation and production of rose oil and related products.
  • C. Akhisar
    Akhisar is a town in western Turkey that occupies the site of the ancient city of Thyatira, one of the early centers of Christianity in Asia Minor.
  • D. Gedera
    Gedera is a town in central Israel known for its agricultural roots and diverse immigrant communities.
  • E. Bergama
    Bergama is a town in western Turkey known for encompassing the archaeological remains of the ancient city of Pergamon, a major Hellenistic and Roman cultural and political center.
  • 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_69c6880ef37881909268a5a7299b9293 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1b74ae081908575c4e47c0ef297 completed March 27, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723c148c88190bf47495b2d105f73 completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:10 p.m.