Triple

T13804192
Position Surface form Disambiguated ID Type / Status
Subject Ghazipur E331718 entity
Predicate additionalOfficialLanguage P5601 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: [Ghazipur, additionalOfficialLanguage, Urdu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urdu
Context triple: [Ghazipur, additionalOfficialLanguage, 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. 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. Sindhi
    Sindhi is an Indo-Aryan language spoken primarily in Pakistan and India, known for its rich literary tradition and distinct script variants.
  • D. Saraiki
    Saraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
  • E. 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.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026c36108190a7436034a730a261 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b08bd7c48190bcdf110ccd27c003 completed May 3, 2026, 8:31 p.m.
Created at: April 9, 2026, 10:12 p.m.