Triple

T36017021

Position	Surface form	Disambiguated ID	Type / Status
Subject	Baha al-Din al-Amili	`E1041870`	entity
Predicate	notableWork	`P4`	FINISHED
Object	al-Fawāʾid al-Ṣamadīyah al-Fawāʾid al-Ṣamadīyah is a renowned Arabic grammar treatise by the Safavid-era scholar Baha al-Din al-Amili, widely studied in traditional Islamic seminaries.	`E2164753`	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-Fawāʾid al-Ṣamadīyah | Statement: [Baha al-Din al-Amili, notableWork, al-Fawāʾid al-Ṣamadīyah]

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-Fawāʾid al-Ṣamadīyah
Triple: [Baha al-Din al-Amili, notableWork, al-Fawāʾid al-Ṣamadīyah]

Generated description

al-Fawāʾid al-Ṣamadīyah is a renowned Arabic grammar treatise by the Safavid-era scholar Baha al-Din al-Amili, widely studied in traditional Islamic seminaries.

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_69f76e2b981881908e4e160607fa82eb`	completed	May 3, 2026, 3:47 p.m.
NER	Named-entity recognition	`batch_69f7ace0a35c819087293a87666b9f07`	completed	May 3, 2026, 8:15 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a38bffe46f08190badbf2a6df84a44f`	completed	June 22, 2026, 4:54 a.m.
NEDg	Description generation	`batch_6a38c088eb848190a35f4cff5101fea5`	completed	June 22, 2026, 4:56 a.m.
NED2	Entity disambiguation (via description)	`batch_6a38c12e3d74819084ff442c6aa8d02a`	completed	June 22, 2026, 4:59 a.m.

Created at: May 3, 2026, 4:07 p.m.