Triple

T4684439
Position Surface form Disambiguated ID Type / Status
Subject Gaziantep Castle E103885 entity
Predicate locatedIn P40 FINISHED
Object Gaziantep E17791 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: Gaziantep | Statement: [Gaziantep Castle, locatedIn, Gaziantep]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaziantep
Context triple: [Gaziantep Castle, locatedIn, 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. Kayseri
    Kayseri is a historic city in central Turkey, known for its Seljuk and Ottoman architectural heritage and its role as a major commercial and cultural center in Anatolia.
  • 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_69bd43debbf08190b4bc372e286ec234 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63829b048190a2044de900ef7a69 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf6c27ce8c81908253c7639207fd3c completed March 22, 2026, 4:12 a.m.
Created at: March 20, 2026, 1:16 p.m.