Triple

T26062185
Position Surface form Disambiguated ID Type / Status
Subject Mother of the Book E657288 entity
Predicate relatedConcept P37 FINISHED
Object Umm al-Qur’an
Umm al-Qur’an is an Islamic term referring to the foundational opening chapter of the Qur’an, Al-Fātiḥah, regarded as the essence and summary of the entire scripture.
 E168926 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: Umm al-Qur’an | Statement: [Mother of the Book, relatedConcept, Umm al-Qur’an]
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: Umm al-Qur’an
Triple: [Mother of the Book, relatedConcept, Umm al-Qur’an]
Generated description
Umm al-Qur’an is an Islamic term referring to the foundational opening chapter of the Qur’an, Al-Fātiḥah, regarded as the essence and summary of the entire scripture.

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_69ee5bbd788481909e22bd7153d0c037 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f606941410819098a15b288273c3e1 completed May 2, 2026, 2:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111b27efc88190b8d908eafb866d7a completed May 23, 2026, 3:12 a.m.
NEDg Description generation batch_6a111c26bd588190bcb5b6acd9978f06 completed May 23, 2026, 3:16 a.m.
NED2 Entity disambiguation (via description) batch_6a111cfb960c8190ab95d50846acfb91 completed May 23, 2026, 3:20 a.m.
Created at: April 26, 2026, 7:18 p.m.