Triple

T8192704
Position Surface form Disambiguated ID Type / Status
Subject Garipçe E191350 entity
Predicate near P350 FINISHED
Object Rumelifeneri E662870 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: Rumelifeneri | Statement: [Garipçe, near, Rumelifeneri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rumelifeneri
Context triple: [Garipçe, near, Rumelifeneri]
  • A. Rumelifeneri chosen
    Rumelifeneri is a coastal village and historic lighthouse area on the European side of the Bosphorus in Istanbul, Turkey.
  • B. Oğuzeli
    Oğuzeli is a town and district in Gaziantep Province in southeastern Turkey, known for its proximity to Gaziantep Oğuzeli International Airport and its role in the region’s agricultural and local trade activities.
  • C. Gürbulak
    Gürbulak is a Turkish border village and crossing point on the frontier with Iran, serving as a key gateway between the two countries.
  • D. Derince
    Derince is an industrial and port city located on the Sea of Marmara in northwestern Turkey.
  • E. Özdamar
    Özdamar is the surname of Emine Sevgi Özdamar, a prominent Turkish-German writer, actress, and director known for her works on migration and cultural identity.
  • 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_69ca82c5b6948190a583c096fb0a6c71 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb5c1d7aa48190adbbce88b3bed1a3 completed March 31, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cceda1b22c8190acc1a2cd0fe36b70 completed April 1, 2026, 10:04 a.m.
Created at: March 30, 2026, 5:42 p.m.