Triple

T4040365
Position Surface form Disambiguated ID Type / Status
Subject Sait Faik Abasıyanık E83930 entity
Predicate notableWork P4 FINISHED
Object Semaver
Semaver is a celebrated short story collection by Turkish writer Sait Faik Abasıyanık, known for its lyrical depictions of everyday Istanbul life and marginalized characters.
 E408855 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: Semaver | Statement: [Sait Faik Abasıyanık, notableWork, Semaver]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Semaver
Context triple: [Sait Faik Abasıyanık, notableWork, Semaver]
  • A. Schueller
    Schueller is a French surname most notably associated with Eugène Schueller, the chemist and entrepreneur who founded the cosmetics company L’Oréal.
  • B. Suter
    Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
  • C. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • D. Ruländer
    Ruländer is a traditional German name for the Pinot Gris grape variety, commonly used for rich, full-bodied white wines.
  • E. Seidler
    Seidler is a surname most notably associated with British-American screenwriter David Seidler, known for writing the film "The King's Speech."
  • 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: Semaver
Triple: [Sait Faik Abasıyanık, notableWork, Semaver]
Generated description
Semaver is a celebrated short story collection by Turkish writer Sait Faik Abasıyanık, known for its lyrical depictions of everyday Istanbul life and marginalized characters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Semaver
Target entity description: Semaver is a celebrated short story collection by Turkish writer Sait Faik Abasıyanık, known for its lyrical depictions of everyday Istanbul life and marginalized characters.
  • A. Schueller
    Schueller is a French surname most notably associated with Eugène Schueller, the chemist and entrepreneur who founded the cosmetics company L’Oréal.
  • B. Suter
    Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
  • C. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • D. Ruländer
    Ruländer is a traditional German name for the Pinot Gris grape variety, commonly used for rich, full-bodied white wines.
  • E. Seidler
    Seidler is a surname most notably associated with British-American screenwriter David Seidler, known for writing the film "The King's Speech."
  • 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.