Triple

T19802672
Position Surface form Disambiguated ID Type / Status
Subject Kahramanmaraş Province E475723 entity
Predicate hasHistoricCity P3786 FINISHED
Object Kahramanmaraş 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: Kahramanmaraş | Statement: [Kahramanmaraş Province, hasHistoricCity, Kahramanmaraş]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kahramanmaraş
Context triple: [Kahramanmaraş Province, hasHistoricCity, Kahramanmaraş]
  • A. Gaziantep
    Gaziantep is a major city in southeastern Turkey known for its rich history, cultural heritage, and renowned pistachio-based cuisine, especially baklava.
  • B. Kütahya
    Kütahya is a historic city in western Turkey known for its Ottoman-era architecture and traditional ceramic and tile production.
  • C. Kahramanmaraş Province chosen
    Kahramanmaraş Province is an administrative region in southern Turkey known for its historic city of Kahramanmaraş and its famous Maraş ice cream.
  • 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e654257cb4819096fb2aa5d1f7fbb0 completed April 20, 2026, 4:28 p.m.
Created at: April 10, 2026, 1:49 p.m.