Triple

T1055017
Position Surface form Disambiguated ID Type / Status
Subject Doabi dialect E22781 entity
Predicate writingSystem P454 FINISHED
Object Gurmukhi script E12238 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: Gurmukhi script | Statement: [Doabi dialect, writingSystem, Gurmukhi script]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gurmukhi script
Context triple: [Doabi dialect, writingSystem, Gurmukhi script]
  • A. Gurmukhi chosen
    Gurmukhi is an Indic writing system primarily used for the Punjabi language and for recording Sikh religious scriptures.
  • B. Shahmukhi script
    Shahmukhi script is a Perso-Arabic–based writing system primarily used for writing the Punjabi language in Pakistan.
  • C. Devanagari script
    Devanagari script is an abugida writing system used for several major South Asian languages, including Hindi, Marathi, Nepali, and Sanskrit.
  • D. 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.
  • E. Eastern Nagari script
    The Eastern Nagari script is an abugida used across eastern South Asia, most prominently for writing the Bengali and Assamese languages.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8d79268819080f3f3f497e91c58 completed March 1, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac66224db481909318add535721977 completed March 7, 2026, 5:53 p.m.
Created at: March 1, 2026, 7:42 p.m.