Triple

T27306591
Position Surface form Disambiguated ID Type / Status
Subject Suhayl ibn Amr E689076 entity
Predicate hadSon P60575 FINISHED
Object Abdullah ibn Suhayl
Abdullah ibn Suhayl was an early companion of the Prophet Muhammad who initially joined the Quraysh at Badr but defected to the Muslims and later fought and died as a martyr in their ranks.
E1819378 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: Abdullah ibn Suhayl | Statement: [Suhayl ibn Amr, hadSon, Abdullah ibn Suhayl]
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: Abdullah ibn Suhayl
Triple: [Suhayl ibn Amr, hadSon, Abdullah ibn Suhayl]
Generated description
Abdullah ibn Suhayl was an early companion of the Prophet Muhammad who initially joined the Quraysh at Badr but defected to the Muslims and later fought and died as a martyr in their ranks.

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_69ef355b931c8190a63cafaf7bcc008b completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627afaf648190b187cafdc6f3e8ce completed May 2, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16415670348190a1894d6204f72a1d completed May 27, 2026, 12:56 a.m.
NEDg Description generation batch_6a16428c40688190a86a99c8c936de3e completed May 27, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_6a164322f1148190b37794a5fc54f184 completed May 27, 2026, 1:04 a.m.
Created at: April 27, 2026, 11:25 a.m.