Triple

T26959329
Position Surface form Disambiguated ID Type / Status
Subject Banu Shayban E678992 entity
Predicate hasNotableMember P304 FINISHED
Object al-Fadl ibn Dukayn
Al-Fadl ibn Dukayn was an early Islamic hadith scholar and reliable transmitter renowned for his contributions to the preservation and dissemination of prophetic traditions.
E1759556 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: al-Fadl ibn Dukayn | Statement: [Banu Shayban, hasNotableMember, al-Fadl ibn Dukayn]
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: al-Fadl ibn Dukayn
Triple: [Banu Shayban, hasNotableMember, al-Fadl ibn Dukayn]
Generated description
Al-Fadl ibn Dukayn was an early Islamic hadith scholar and reliable transmitter renowned for his contributions to the preservation and dissemination of prophetic traditions.

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_69eeeb4e75f08190b14fc91ca4a91488 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f620eadb4c8190bdfec5d1d5f7fdc1 completed May 2, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1253666df081908c7020659375bc2b completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a125433c0288190ab1e54c3d763468d completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a1254f46d288190aa6f45f8c8e9007d completed May 24, 2026, 1:31 a.m.
Created at: April 27, 2026, 6:29 a.m.