Triple

T4999255
Position Surface form Disambiguated ID Type / Status
Subject Sarojini Naidu E112326 entity
Predicate languageOfWorkOrName P15 FINISHED
Object Urdu E6054 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: Urdu | Statement: [Sarojini Naidu, languageOfWorkOrName, Urdu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urdu
Context triple: [Sarojini Naidu, languageOfWorkOrName, Urdu]
  • A. Urdu language chosen
    Urdu is a major South Asian language, written in a Perso-Arabic script and widely used in Pakistan and parts of India in literature, media, and everyday communication.
  • B. Sindhi
    Sindhi is an Indo-Aryan language spoken primarily in Pakistan and India, known for its rich literary tradition and distinct script variants.
  • C. Saraiki
    Saraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
  • D. Balochi
    Balochi is an Iranian language spoken primarily by the Baloch people across Pakistan, Iran, and Afghanistan, with several dialects and a rich oral literary tradition.
  • E. Punjabi
    Punjabi refers to the ethnolinguistic group native to the Punjab region of South Asia, known for its distinct language, culture, and traditions shared across parts of India and Pakistan.
  • 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_69bd4432b32c81909f3b3c6bd10f0653 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd72bc100c81908c3e02726e1ef8f6 completed March 20, 2026, 4:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69be8a1891c48190b85bec5e97f75e44 completed March 21, 2026, 12:07 p.m.
Created at: March 20, 2026, 1:34 p.m.