Triple

T20837140
Position Surface form Disambiguated ID Type / Status
Subject Musa Qala E512988 entity
Predicate hasLanguage P15 FINISHED
Object Pashto 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: Pashto | Statement: [Musa Qala, hasLanguage, Pashto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pashto
Context triple: [Musa Qala, hasLanguage, Pashto]
  • A. Pashto language chosen
    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.
  • B. 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.
  • 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. Zazaki
    Zazaki is an Indo-Iranian language spoken primarily in eastern Turkey, often associated with the Zaza people and considered one of the main Kurdish-related dialects or languages.
  • E. Saraiki
    Saraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
  • 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_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c3280a1881909a86d1fe498aee50 completed April 21, 2026, 12:22 a.m.
Created at: April 16, 2026, 12:42 p.m.