Triple

T20130223
Position Surface form Disambiguated ID Type / Status
Subject Shahi Qila (Royal Fort) E490868 entity
Predicate languageOfName P15 FINISHED
Object Urdu NE NERFINISHED

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: [Shahi Qila (Royal Fort), languageOfName, Urdu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urdu
Context triple: [Shahi Qila (Royal Fort), languageOfName, 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 (2 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6676183dc8190b65d0def681aaa1e completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:31 p.m.