Triple

T15942712
Position Surface form Disambiguated ID Type / Status
Subject Mirpuri E386604 entity
Predicate script P505 FINISHED
Object Shahmukhi E27965 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: Shahmukhi | Statement: [Mirpuri, script, Shahmukhi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shahmukhi
Context triple: [Mirpuri, script, Shahmukhi]
  • A. Shahmukhi script chosen
    Shahmukhi script is a Perso-Arabic–based writing system primarily used for writing the Punjabi language in Pakistan.
  • B. Multani script
    Multani script is a historical Brahmic writing system once used primarily for the Multani language and mercantile records in the Multan region of the Indian subcontinent.
  • C. Akshara Nagari
    Akshara Nagari is a popular moniker for Kottayam, a Kerala town renowned for its high literacy, rich publishing tradition, and educational institutions.
  • D. Khudabadi script
    The Khudabadi script is a historical writing system used primarily by Sindhi-speaking merchant communities of the Indian subcontinent for commercial and everyday purposes.
  • E. Brahmi script
    The Brahmi script is one of the oldest writing systems of the Indian subcontinent, serving as the ancestor of most modern South and Southeast Asian scripts.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156cefe948190af40eac92983edbc completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe7455c48190bfad24eb8905426d completed May 9, 2026, 11:08 p.m.
Created at: April 10, 2026, 4:53 a.m.