Triple

T294018
Position Surface form Disambiguated ID Type / Status
Subject Urdu E6054 entity
Predicate writingSystem P454 FINISHED
Object Nastaʿlīq script E27655 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: Nastaʿlīq script | Statement: [Urdu, writingSystem, Nastaʿlīq script]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nastaʿlīq script
Context triple: [Urdu, writingSystem, Nastaʿlīq script]
  • A. Nastaʿlīq chosen
    Nastaʿlīq is an elegant, flowing calligraphic style of the Perso-Arabic script historically associated with Persian literary and artistic traditions.
  • B. Diwani script
    Diwani script is an ornate Ottoman-era style of Arabic calligraphy characterized by its intricate, flowing lines and dense, decorative composition often used in royal decrees and official documents.
  • C. Thuluth script
    Thuluth script is a large, elegant, and highly cursive style of Arabic calligraphy traditionally used for architectural inscriptions, Qur’anic headings, and decorative works.
  • D. Naskh script
    Naskh script is a widely used, highly legible style of Arabic calligraphy commonly employed in printed texts, books, and everyday writing.
  • E. Shahmukhi script
    Shahmukhi script is a Perso-Arabic–based writing system primarily used for writing the Punjabi language in Pakistan.
  • 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_69a2e79114b081909490b3bf5a5dbb51 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2e978420881908488df342a7d5e90 completed Feb. 28, 2026, 1:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3a5d514388190ac0f748a406ae43e completed March 1, 2026, 2:35 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.