Triple

T346728
Position Surface form Disambiguated ID Type / Status
Subject Pashto language E6957 entity
Predicate hasLoanwordsFrom P506 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: [Pashto language, hasLoanwordsFrom, Urdu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urdu language
Context triple: [Pashto language, hasLoanwordsFrom, 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. 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.
  • C. Saraiki
    Saraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
  • D. Sindhi
    Sindhi is an Indo-Aryan language spoken primarily in Pakistan and India, known for its rich literary tradition and distinct script variants.
  • E. Punjabi language
    Punjabi language is an Indo-Aryan language widely spoken in the Punjab region of India and Pakistan and among large diaspora communities worldwide.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eb1a37c08190b1380f6bf8513a37 completed Feb. 28, 2026, 1:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3d7eb6b708190b0dff991c101104f completed March 1, 2026, 6:08 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.