Triple

T14550148
Position Surface form Disambiguated ID Type / Status
Subject Iqra E341393 entity
Predicate surahName P15360 FINISHED
Object Al-Alaq E341392 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-Alaq | Statement: [Iqra, surahName, Al-Alaq]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Al-Alaq
Context triple: [Iqra, surahName, Al-Alaq]
  • A. Al-Alaq chosen
    Al-Alaq is the 96th chapter of the Qur’an, renowned for containing the first verses revealed to the Prophet Muhammad and emphasizing reading, knowledge, and human creation.
  • B. Pluma
    Pluma is the lightweight text editor for the MATE desktop environment, designed as a continuation of the classic GNOME 2 "gedit" editor.
  • C. Alif
    Alif is one of the official mascots of Expo 2020 Dubai, represented as a futuristic robot embodying innovation and mobility.
  • D. Al-Qalam
    Al-Qalam is the transliterated Arabic title of the 68th chapter of the Qur’an, known for its emphasis on moral character and the story of the People of the Garden.
  • E. Al Boraq
    Al Boraq is Morocco’s high-speed train service that connects major cities such as Casablanca and Tangier.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2ed2b4c8190945bd26531c71f1f completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a6344b08190a3c1124c6dd7da96 completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:23 a.m.