Triple

T14169699
Position Surface form Disambiguated ID Type / Status
Subject Kırşehir Province E351173 entity
Predicate administrativeCenter P1474 FINISHED
Object Kırşehir
Kırşehir is a city in central Turkey known for its historical heritage and role as a regional cultural and economic hub.
E351173 NE FINISHED

How this triple was built (4 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: Kırşehir | Statement: [Kırşehir Province, administrativeCenter, Kırşehir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kırşehir
Context triple: [Kırşehir Province, administrativeCenter, Kırşehir]
  • A. Çankırı
    Çankırı is a small provincial city in north-central Turkey known for its historical fortifications, salt mines, and location on the Anatolian plateau.
  • B. Kırşehir Province
    Kırşehir Province is a central Anatolian province of Turkey known for its agricultural economy and historical and cultural heritage.
  • C. Kilis
    Kilis is a small Turkish city near the Syrian border known for its strategic location, cross-border trade, and distinctive regional cuisine.
  • D. Aksaray
    Aksaray is a historic city in central Turkey known for its location on the ancient Silk Road and its proximity to the Cappadocia region.
  • E. Kütahya
    Kütahya is a historic city in western Turkey known for its Ottoman-era architecture and traditional ceramic and tile production.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kırşehir
Triple: [Kırşehir Province, administrativeCenter, Kırşehir]
Generated description
Kırşehir is a city in central Turkey known for its historical heritage and role as a regional cultural and economic hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kırşehir
Target entity description: Kırşehir is a city in central Turkey known for its historical heritage and role as a regional cultural and economic hub.
  • A. Çankırı
    Çankırı is a small provincial city in north-central Turkey known for its historical fortifications, salt mines, and location on the Anatolian plateau.
  • B. Kırşehir Province chosen
    Kırşehir Province is a central Anatolian province of Turkey known for its agricultural economy and historical and cultural heritage.
  • C. Kilis
    Kilis is a small Turkish city near the Syrian border known for its strategic location, cross-border trade, and distinctive regional cuisine.
  • D. Aksaray
    Aksaray is a historic city in central Turkey known for its location on the ancient Silk Road and its proximity to the Cappadocia region.
  • E. Kütahya
    Kütahya is a historic city in western Turkey known for its Ottoman-era architecture and traditional ceramic and tile production.
  • F. None of above.

Provenance (5 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b472288190b4a271daa54aa6cd completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c2a938081909ccd9fe7c5021dc6 completed May 9, 2026, 3 p.m.
NEDg Description generation batch_69ff4d7e60dc8190aa80cb269b1811bc completed May 9, 2026, 3:06 p.m.
NED2 Entity disambiguation (via description) batch_69ff4e03e8748190a23e7577accaf04a completed May 9, 2026, 3:08 p.m.
Created at: April 10, 2026, 1:01 a.m.