Triple

T26849455
Position Surface form Disambiguated ID Type / Status
Subject Türk Edebiyatında İlk Mutasavvıflar E676018 entity
Predicate examines P170 FINISHED
Object Süleyman Hakim Ata
Süleyman Hakim Ata was an early Turkic Sufi poet and mystic, regarded as one of the foundational figures of Islamic mystical literature in Central Asia.
E1768904 NE FINISHED

How this triple was built (2 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: Süleyman Hakim Ata | Statement: [Türk Edebiyatında İlk Mutasavvıflar, examines, Süleyman Hakim Ata]
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: Süleyman Hakim Ata
Triple: [Türk Edebiyatında İlk Mutasavvıflar, examines, Süleyman Hakim Ata]
Generated description
Süleyman Hakim Ata was an early Turkic Sufi poet and mystic, regarded as one of the foundational figures of Islamic mystical literature in Central Asia.

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_69eee9b9d7708190a15d7485709ae981 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61b90393c819090595eac8e538e05 completed May 2, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7b21a608190b5e6a080d56546ad completed May 24, 2026, 7:24 a.m.
NEDg Description generation batch_6a12a8b8ec608190846c55dabeec801a completed May 24, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_6a12a951f04881909419d5b9d41d5c79 completed May 24, 2026, 7:31 a.m.
Created at: April 27, 2026, 5:15 a.m.