Triple

T25672497
Position Surface form Disambiguated ID Type / Status
Subject Ibn Shihab al-Zuhri E643715 entity
Predicate teacherOf P48 FINISHED
Object Yunus ibn Yazid al-Ayli
Yunus ibn Yazid al-Ayli was an early Islamic scholar and hadith transmitter known for narrating traditions from prominent authorities of the first generations of Muslims.
E1693174 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: Yunus ibn Yazid al-Ayli | Statement: [Ibn Shihab al-Zuhri, teacherOf, Yunus ibn Yazid al-Ayli]
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: Yunus ibn Yazid al-Ayli
Triple: [Ibn Shihab al-Zuhri, teacherOf, Yunus ibn Yazid al-Ayli]
Generated description
Yunus ibn Yazid al-Ayli was an early Islamic scholar and hadith transmitter known for narrating traditions from prominent authorities of the first generations of Muslims.

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_69e77e7f69808190ad27df1006f6037a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fb3389ac819092997022ed2bc2f8 completed May 2, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10cbecd6948190ba672a6a966c6432 completed May 22, 2026, 9:34 p.m.
NEDg Description generation batch_6a10cd1f2f1c8190acac62d516c5d450 completed May 22, 2026, 9:39 p.m.
NED2 Entity disambiguation (via description) batch_6a10ce0317348190b9b75259df58a264 completed May 22, 2026, 9:43 p.m.
Created at: April 21, 2026, 7:30 p.m.