Triple

T9989543
Position Surface form Disambiguated ID Type / Status
Subject Urdu literature E196850 entity
Predicate usesLanguage P238 FINISHED
Object Urdu language 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 language | Statement: [Urdu literature, usesLanguage, Urdu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urdu language
Context triple: [Urdu literature, usesLanguage, Urdu language]
  • 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. Abbottabadi Hindko
    Abbottabadi Hindko is a regional variety of the Hindko language spoken primarily in and around the city of Abbottabad in northern Pakistan.
  • C. Pashto language
    Pashto is an Eastern Iranian language spoken primarily in Afghanistan and Pakistan, serving as one of Afghanistan’s official languages and a key marker of Pashtun ethnic identity.
  • D. Saraiki
    Saraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
  • E. Sindhi
    Sindhi is an Indo-Aryan language spoken primarily in Pakistan and India, known for its rich literary tradition and distinct script variants.
  • 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_69ca82f1678c819093d06320a05f16a4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdc79f3df08190ab3094ad1cd5490f completed April 2, 2026, 1:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26a21b2388190b16f0aa142846599 completed April 5, 2026, 1:56 p.m.
Created at: March 30, 2026, 8:50 p.m.