Triple

T2423713
Position Surface form Disambiguated ID Type / Status
Subject Cabinet of Pakistan E53476 entity
Predicate languageUsed P238 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: [Cabinet of Pakistan, languageUsed, Urdu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urdu
Context triple: [Cabinet of Pakistan, languageUsed, 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. Urdu literature
    Urdu literature is the body of written works produced in the Urdu language, encompassing poetry, prose, and drama that reflect the cultural, religious, and social life of South Asia.
  • 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc973aee08190b543492f436f3fe5 completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf5e33208190a6899e6672b3daeb completed March 9, 2026, 12:38 p.m.
Created at: March 6, 2026, 9:42 p.m.