Triple

T5629270
Position Surface form Disambiguated ID Type / Status
Subject Kashmiri language E147793 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: [Kashmiri language, hasLoanwordsFrom, Urdu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urdu language
Context triple: [Kashmiri 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_69c00907bc8881909ed760d3ed73ef35 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0223b1e54819099fe5fc84ed17a88 completed March 22, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d654c6c819087c1bcb4eb9530d0 completed March 22, 2026, 8:13 p.m.
Created at: March 22, 2026, 3:40 p.m.