Triple

T12151209
Position Surface form Disambiguated ID Type / Status
Subject Şanlıurfa Province E289457 entity
Predicate contains P35 FINISHED
Object Viranşehir
Viranşehir is a town and district in southeastern Turkey known for its agricultural economy and location within Şanlıurfa Province near the Syrian border.
E1035979 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: Viranşehir | Statement: [Şanlıurfa Province, contains, Viranşehir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viranşehir
Context triple: [Şanlıurfa Province, contains, Viranşehir]
  • A. Suşehri
    Suşehri is a town and district in northeastern Turkey known for its location within Sivas Province and its surrounding mountainous landscape.
  • B. Yüreğir
    Yüreğir is a metropolitan district and municipality of Adana Province in southern Turkey, located on the eastern bank of the Seyhan River and forming part of the city of Adana.
  • C. Toprakkale
    Toprakkale is an ancient fortress and archaeological site in eastern Turkey that served as a significant center of the Iron Age Kingdom of Urartu.
  • D. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • E. Isparta
    Isparta is a city in southwestern Turkey known for its rose cultivation and production of rose oil and related products.
  • 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: Viranşehir
Triple: [Şanlıurfa Province, contains, Viranşehir]
Generated description
Viranşehir is a town and district in southeastern Turkey known for its agricultural economy and location within Şanlıurfa Province near the Syrian border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Viranşehir
Target entity description: Viranşehir is a town and district in southeastern Turkey known for its agricultural economy and location within Şanlıurfa Province near the Syrian border.
  • A. Suşehri
    Suşehri is a town and district in northeastern Turkey known for its location within Sivas Province and its surrounding mountainous landscape.
  • B. Yüreğir
    Yüreğir is a metropolitan district and municipality of Adana Province in southern Turkey, located on the eastern bank of the Seyhan River and forming part of the city of Adana.
  • C. Toprakkale
    Toprakkale is an ancient fortress and archaeological site in eastern Turkey that served as a significant center of the Iron Age Kingdom of Urartu.
  • D. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • E. Isparta
    Isparta is a city in southwestern Turkey known for its rose cultivation and production of rose oil and related products.
  • F. None of above. chosen

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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915ae736c8190aaab05efb93c5854 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f726570a2481909f417be6e38d283a completed May 3, 2026, 10:41 a.m.
NEDg Description generation batch_69f726e03c4081908a0a07729eb30906 completed May 3, 2026, 10:43 a.m.
NED2 Entity disambiguation (via description) batch_69f727d063c4819084b4990a0d759f79 completed May 3, 2026, 10:47 a.m.
Created at: April 8, 2026, 9:49 p.m.