Triple

T36561577

Position	Surface form	Disambiguated ID	Type / Status
Subject	سلطان المغرب	`E901851`	entity
Predicate	مرتبط_بـ	`P37`	FINISHED
Object	الدولة المرابطية الدولة المرابطية هي دولة إسلامية أمازيغية قامت في المغرب والأندلس بين القرنين الحادي عشر والثاني عشر الميلاديين واشتهرت بنشر المذهب المالكي وتوحيد أجزاء واسعة من المغرب العربي والأندلس.	`E2188632`	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: الدولة المرابطية | Statement: [سلطان المغرب, مرتبط_بـ, الدولة المرابطية]

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: الدولة المرابطية
Triple: [سلطان المغرب, مرتبط_بـ, الدولة المرابطية]

Generated description

الدولة المرابطية هي دولة إسلامية أمازيغية قامت في المغرب والأندلس بين القرنين الحادي عشر والثاني عشر الميلاديين واشتهرت بنشر المذهب المالكي وتوحيد أجزاء واسعة من المغرب العربي والأندلس.

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_69f76e634e9481908c9ba1b87ab87c26`	completed	May 3, 2026, 3:48 p.m.
NER	Named-entity recognition	`batch_69f7c27c86188190b1e1a9249a906704`	completed	May 3, 2026, 9:47 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a39e6f41f188190927892b7759a0efa`	completed	June 23, 2026, 1:52 a.m.
NEDg	Description generation	`batch_6a39e84eb7c881909d0c68c0dbbaddb8`	completed	June 23, 2026, 1:58 a.m.
NED2	Entity disambiguation (via description)	`batch_6a39ead0e6588190bcc077c11b7b049a`	completed	June 23, 2026, 2:09 a.m.

Created at: May 3, 2026, 4:11 p.m.