Triple

T4516729
Position Surface form Disambiguated ID Type / Status
Subject Lenasia E102169 entity
Predicate language P15 FINISHED
Object Gujarati E8599 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: Gujarati | Statement: [Lenasia, language, Gujarati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gujarati
Context triple: [Lenasia, language, Gujarati]
  • A. Gujarati chosen
    Gujarati is an Indo-Aryan language primarily spoken in the Indian state of Gujarat and by Gujarati communities worldwide.
  • B. Hindi
    Hindi is an Indo-Aryan language widely spoken across northern and central India and used in government, education, media, and popular culture.
  • C. Sindhi
    Sindhi is an Indo-Aryan language spoken primarily in Pakistan and India, known for its rich literary tradition and distinct script variants.
  • D. Sant Bhasha
    Sant Bhasha is a historical North Indian devotional literary language used in Sikh and related spiritual poetry, written in the Gurmukhi script.
  • E. Gujarati script
    The Gujarati script is an abugida used primarily to write the Gujarati language and related Indo-Aryan languages, derived from the Devanagari script and characterized by the absence of the horizontal headline.
  • 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_69bd43d6251c81909deecce3e6e9d69c completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5726983c8190bca116eeee54241c completed March 20, 2026, 2:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f93a6808190bc1290232998184c completed March 20, 2026, 5:10 p.m.
Created at: March 20, 2026, 1:02 p.m.