Triple

T24259243
Position Surface form Disambiguated ID Type / Status
Subject ʿAbd al-Karim ibn Hawazin al-Qushayri E604653 entity
Predicate studentOf P48 FINISHED
Object Abu Bakr ibn Furak
Abu Bakr ibn Furak was an influential 10th–11th century Ashʿarī theologian and Shāfiʿī jurist known for his works on Islamic creed and kalām.
E1636830 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: Abu Bakr ibn Furak | Statement: [ʿAbd al-Karim ibn Hawazin al-Qushayri, studentOf, Abu Bakr ibn Furak]
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: Abu Bakr ibn Furak
Triple: [ʿAbd al-Karim ibn Hawazin al-Qushayri, studentOf, Abu Bakr ibn Furak]
Generated description
Abu Bakr ibn Furak was an influential 10th–11th century Ashʿarī theologian and Shāfiʿī jurist known for his works on Islamic creed and kalām.

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_69e29544c29c8190b023606eafe5d36a completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28c6592688190a9c6850a2e979858 completed April 29, 2026, 10:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee563c6881909b2a31c28d505e7b completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0fef072b0c8190901ca4b63dc282db completed May 22, 2026, 5:52 a.m.
NED2 Entity disambiguation (via description) batch_6a0fef57bc408190a9c407a8b547ee36 completed May 22, 2026, 5:53 a.m.
Created at: April 18, 2026, 12:06 a.m.