Triple

T8864772
Position Surface form Disambiguated ID Type / Status
Subject Abu Ali Ibn Muqla E210989 entity
Predicate alsoKnownAs P39 FINISHED
Object Ibn Muqlah E40305 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: Ibn Muqlah | Statement: [Abu Ali Ibn Muqla, alsoKnownAs, Ibn Muqlah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ibn Muqlah
Context triple: [Abu Ali Ibn Muqla, alsoKnownAs, Ibn Muqlah]
  • A. Al-Bujairi
    Al-Bujairi is a historic district in Diriyah, Saudi Arabia, known for its restored traditional architecture, cultural attractions, and scenic views overlooking the Wadi Hanifah.
  • B. Ibn Muqla chosen
    Ibn Muqla was a 10th-century Abbasid vizier and master calligrapher renowned for codifying the proportional rules that shaped classical Arabic scripts, especially Naskh.
  • C. Ibn al-Salah
    Ibn al-Salah was a prominent 13th-century Kurdish Muslim hadith scholar and jurist best known for his foundational work "Muqaddimah Ibn al-Salah" on hadith sciences.
  • D. Ibn Juzayy
    Ibn Juzayy was a 14th-century Andalusian scholar and writer best known for compiling and editing the famous travel account of the explorer Ibn Battuta.
  • E. Ibn al-Bawwab
    Ibn al-Bawwab was an influential 10th–11th century Persian calligrapher renowned for refining and codifying classical Arabic scripts, particularly in Qur’anic manuscripts.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610569d08190b108107dfe397f18 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69d02f88db0881909975af03ed2f3d84 completed April 3, 2026, 9:22 p.m.
Created at: March 30, 2026, 6:51 p.m.