Triple

T26704651
Position Surface form Disambiguated ID Type / Status
Subject Hishām ibn al-Mughīrah E673254 entity
Predicate father P120 FINISHED
Object al-Mughīrah ibn ʿAbd Allāh
al-Mughīrah ibn ʿAbd Allāh was a prominent pre-Islamic leader of the Quraysh tribe in Mecca and an ancestor of several notable figures in early Islamic history.
 E1771957 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-Mughīrah ibn ʿAbd Allāh | Statement: [Hishām ibn al-Mughīrah, father, al-Mughīrah ibn ʿAbd Allāh]
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-Mughīrah ibn ʿAbd Allāh
Triple: [Hishām ibn al-Mughīrah, father, al-Mughīrah ibn ʿAbd Allāh]
Generated description
al-Mughīrah ibn ʿAbd Allāh was a prominent pre-Islamic leader of the Quraysh tribe in Mecca and an ancestor of several notable figures in early Islamic history.

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_69eecda2b49c8190a6c481cfc4c07954 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6178209548190aa912801975c105f completed May 2, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b215f1548190bf7c0b0c7ff090af completed May 24, 2026, 8:08 a.m.
NEDg Description generation batch_6a12b2fc96848190b6f0e000f159a779 completed May 24, 2026, 8:12 a.m.
NED2 Entity disambiguation (via description) batch_6a12b3573a6c819093c3df4feaa23f0a completed May 24, 2026, 8:14 a.m.
Created at: April 27, 2026, 3:33 a.m.