Triple

T2267745
Position Surface form Disambiguated ID Type / Status
Subject Harish-Chandra E50185 entity
Predicate nativeLanguage P151 FINISHED
Object Hindi E5054 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: Hindi | Statement: [Harish-Chandra, nativeLanguage, Hindi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hindi
Context triple: [Harish-Chandra, nativeLanguage, Hindi]
  • A. Hindi chosen
    Hindi is an Indo-Aryan language widely spoken across northern and central India and used in government, education, media, and popular culture.
  • B. Gujarati
    Gujarati is an Indo-Aryan language primarily spoken in the Indian state of Gujarat and by Gujarati communities worldwide.
  • C. Sant Bhasha
    Sant Bhasha is a historical North Indian devotional literary language used in Sikh and related spiritual poetry, written in the Gurmukhi script.
  • D. Hindko
    Hindko is a group of Indo-Aryan dialects spoken primarily in northern Pakistan, especially in parts of Khyber Pakhtunkhwa and Azad Kashmir.
  • E. Maithili
    Maithili is an Indo-Aryan language spoken primarily in the eastern Indian state of Bihar and neighboring regions, with a rich literary tradition and official recognition in India.
  • 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_69a88b01e0048190ba96431b5f990ba9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1bbb49c8190822c7d809375e879 completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71d492a48190be58396831e87ea0 completed March 9, 2026, 7:08 a.m.
Created at: March 4, 2026, 7:48 p.m.