Triple

T14364851
Position Surface form Disambiguated ID Type / Status
Subject Eskişehir Province E356204 entity
Predicate contains P35 FINISHED
Object Sivrihisar
Sivrihisar is a historic town and district in central Turkey known for its traditional Ottoman architecture and cultural heritage.
E1095867 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: Sivrihisar | Statement: [Eskişehir Province, contains, Sivrihisar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sivrihisar
Context triple: [Eskişehir Province, contains, Sivrihisar]
  • A. Sarikoli
    Sarikoli is an Eastern Iranian language spoken primarily by the Tajik ethnic community in the Tashkurgan region of Xinjiang, China.
  • B. Kehama
    Kehama is the powerful and tyrannical sorcerer-rajah who serves as the central antagonist in Robert Southey’s epic poem "The Curse of Kehama."
  • C. Makrakomi
    Makrakomi is a town and municipality in Central Greece, situated in the regional unit of Phthiotis.
  • D. Karakilise
    Karakilise is a historical name for the city now known as Ağrı in eastern Turkey.
  • E. Gülnar
    Gülnar is a rural district and town in southern Turkey known for its mountainous terrain and agricultural economy within Mersin Province.
  • 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: Sivrihisar
Triple: [Eskişehir Province, contains, Sivrihisar]
Generated description
Sivrihisar is a historic town and district in central Turkey known for its traditional Ottoman architecture and cultural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sivrihisar
Target entity description: Sivrihisar is a historic town and district in central Turkey known for its traditional Ottoman architecture and cultural heritage.
  • A. Sarikoli
    Sarikoli is an Eastern Iranian language spoken primarily by the Tajik ethnic community in the Tashkurgan region of Xinjiang, China.
  • B. Kehama
    Kehama is the powerful and tyrannical sorcerer-rajah who serves as the central antagonist in Robert Southey’s epic poem "The Curse of Kehama."
  • C. Makrakomi
    Makrakomi is a town and municipality in Central Greece, situated in the regional unit of Phthiotis.
  • D. Karakilise
    Karakilise is a historical name for the city now known as Ağrı in eastern Turkey.
  • E. Gülnar
    Gülnar is a rural district and town in southern Turkey known for its mountainous terrain and agricultural economy within Mersin Province.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fad48748190a0f34ca4d02f9a3c completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c4cb0c4819094d59b4b1d43588b completed May 8, 2026, 2:37 a.m.
NEDg Description generation batch_69fd4d912ff08190b3594dd134ef7e40 completed May 8, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_69fd4e7e7c508190a42070a2f2b33425 completed May 8, 2026, 2:46 a.m.
Created at: April 10, 2026, 1:15 a.m.