Triple

T19738976
Position Surface form Disambiguated ID Type / Status
Subject Şahinbey E474061 entity
Predicate partOf P40 FINISHED
Object Gaziantep 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: Gaziantep | Statement: [Şahinbey, partOf, Gaziantep]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaziantep
Context triple: [Şahinbey, partOf, Gaziantep]
  • A. Gaziantep chosen
    Gaziantep is a major city in southeastern Turkey known for its rich history, cultural heritage, and renowned pistachio-based cuisine, especially baklava.
  • B. Antakya
    Antakya is a city in southern Turkey, historically known as Antioch, renowned as an important center of Hellenistic, Roman, and early Christian civilization.
  • C. Şanlıurfa
    Şanlıurfa is a historic city in southeastern Turkey, traditionally identified with the ancient city of Edessa and renowned for its rich religious and cultural heritage.
  • D. Kilis
    Kilis is a small Turkish city near the Syrian border known for its strategic location, cross-border trade, and distinctive regional cuisine.
  • E. Diyarbekir
    Diyarbekir is a historic city in southeastern Turkey, widely known today as Diyarbakır and notable for its ancient basalt city walls and rich Kurdish and Ottoman heritage.
  • 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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6515f6efc8190a3da113847464399 completed April 20, 2026, 4:16 p.m.
Created at: April 10, 2026, 1:47 p.m.