Triple

T5489233
Position Surface form Disambiguated ID Type / Status
Subject Guru Arjan E123658 entity
Predicate scriptUsed P2367 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: [Guru Arjan, scriptUsed, Gurmukhi script]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gurmukhi script
Context triple: [Guru Arjan, scriptUsed, 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. Ol Chiki script
    Ol Chiki script is an alphabetic writing system specifically created in the 20th century for the Santhali language, used primarily by the Santal people of eastern India and neighboring regions.
  • D. Nandinagari script
    Nandinagari script is a historical Brahmic script of southern India, primarily used to write Sanskrit and related languages in the Deccan region.
  • E. Devanagari script
    Devanagari script is an abugida writing system used for several major South Asian languages, including Hindi, Marathi, Nepali, and Sanskrit.
  • 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_69bd464a2d908190869324ce176779c8 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd927c946c8190aef40679199fede3 completed March 20, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf6c884c0c8190b2f8345a5017c71f completed March 22, 2026, 4:14 a.m.
Created at: March 20, 2026, 2:10 p.m.