Triple

T4040366
Position Surface form Disambiguated ID Type / Status
Subject Sait Faik Abasıyanık E83930 entity
Predicate notableWork P4 FINISHED
Object Sarnıç
Sarnıç is a short story collection by renowned Turkish writer Sait Faik Abasıyanık, known for its vivid portrayals of everyday life and marginalized characters in Istanbul.
 E408856 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: Sarnıç | Statement: [Sait Faik Abasıyanık, notableWork, Sarnıç]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sarnıç
Context triple: [Sait Faik Abasıyanık, notableWork, Sarnıç]
  • A. Sagarejo
    Sagarejo is a town in eastern Georgia that serves as an important local center in the Kakheti wine-producing region.
  • B. Demerdzhi
    Demerdzhi is a notable mountain massif in Crimea, famous for its striking rock formations and scenic landscapes.
  • C. Balçova
    Balçova is a coastal district of İzmir, Turkey, known for its thermal springs, residential areas, and proximity to the city center.
  • D. Sarikoli
    Sarikoli is an Eastern Iranian language spoken primarily by the Tajik ethnic community in the Tashkurgan region of Xinjiang, China.
  • E. Söğütlüçeşme
    Söğütlüçeşme is a neighborhood and major transport hub on Istanbul’s Asian side, known especially for its Marmaray and metrobus connections.
  • 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: Sarnıç
Triple: [Sait Faik Abasıyanık, notableWork, Sarnıç]
Generated description
Sarnıç is a short story collection by renowned Turkish writer Sait Faik Abasıyanık, known for its vivid portrayals of everyday life and marginalized characters in Istanbul.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sarnıç
Target entity description: Sarnıç is a short story collection by renowned Turkish writer Sait Faik Abasıyanık, known for its vivid portrayals of everyday life and marginalized characters in Istanbul.
  • A. Sagarejo
    Sagarejo is a town in eastern Georgia that serves as an important local center in the Kakheti wine-producing region.
  • B. Demerdzhi
    Demerdzhi is a notable mountain massif in Crimea, famous for its striking rock formations and scenic landscapes.
  • C. Balçova
    Balçova is a coastal district of İzmir, Turkey, known for its thermal springs, residential areas, and proximity to the city center.
  • D. Sarikoli
    Sarikoli is an Eastern Iranian language spoken primarily by the Tajik ethnic community in the Tashkurgan region of Xinjiang, China.
  • E. Söğütlüçeşme
    Söğütlüçeşme is a neighborhood and major transport hub on Istanbul’s Asian side, known especially for its Marmaray and metrobus connections.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb39400881909d0f5430f04e441c completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55649b75c819086b272f56ac73be4 completed March 14, 2026, 12:36 p.m.
NEDg Description generation batch_69b55a1974348190b6c8ca74fb9da47e completed March 14, 2026, 12:52 p.m.
NED2 Entity disambiguation (via description) batch_69b55a828d7881908e3e9a14bc77103c completed March 14, 2026, 12:54 p.m.
Created at: March 9, 2026, 3:37 p.m.