Triple

T12151214
Position Surface form Disambiguated ID Type / Status
Subject Şanlıurfa Province E289457 entity
Predicate contains P35 FINISHED
Object Hilvan
Hilvan is a district and town in southeastern Turkey known for its agricultural economy and location within Şanlıurfa Province.
 E966903 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: Hilvan | Statement: [Şanlıurfa Province, contains, Hilvan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hilvan
Context triple: [Şanlıurfa Province, contains, Hilvan]
  • A. Halsua
    Halsua is a small rural municipality in western Finland known for its forests, lakes, and traditional Finnish countryside.
  • B. Hemsila
    Hemsila is a river in the Norwegian municipality of Hemsedal, known for its scenic valley course and popular trout fishing.
  • C. Huelén
    Huelén is the former indigenous name for Cerro Santa Lucía, a historic hill and urban park in central Santiago, Chile.
  • D. Heltermaa
    Heltermaa is a small port village on the eastern coast of Hiiumaa Island in Estonia, serving as a key ferry connection to the mainland.
  • E. Hilgay
    Hilgay is a small village and civil parish in Norfolk, England, situated in the Fens and known for its agricultural landscape and riverside setting.
  • 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: Hilvan
Triple: [Şanlıurfa Province, contains, Hilvan]
Generated description
Hilvan is a district and town in southeastern Turkey known for its agricultural economy and location within Şanlıurfa Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hilvan
Target entity description: Hilvan is a district and town in southeastern Turkey known for its agricultural economy and location within Şanlıurfa Province.
  • A. Halsua
    Halsua is a small rural municipality in western Finland known for its forests, lakes, and traditional Finnish countryside.
  • B. Hemsila
    Hemsila is a river in the Norwegian municipality of Hemsedal, known for its scenic valley course and popular trout fishing.
  • C. Huelén
    Huelén is the former indigenous name for Cerro Santa Lucía, a historic hill and urban park in central Santiago, Chile.
  • D. Heltermaa
    Heltermaa is a small port village on the eastern coast of Hiiumaa Island in Estonia, serving as a key ferry connection to the mainland.
  • E. Hilgay
    Hilgay is a small village and civil parish in Norfolk, England, situated in the Fens and known for its agricultural landscape and riverside setting.
  • 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_69f5f69aa2e88190aaa58468571d6dad completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f601e0777081909e1212436680a10d completed May 2, 2026, 1:53 p.m.
NED2 Entity disambiguation (via description) batch_69f602a21f948190849839301f49d55a completed May 2, 2026, 1:56 p.m.
Created at: April 8, 2026, 9:49 p.m.