Triple

T6016837
Position Surface form Disambiguated ID Type / Status
Subject Middle Iranian languages E133967 entity
Predicate influenced P9 FINISHED
Object Pashto E6957 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: Pashto | Statement: [Middle Iranian languages, influenced, Pashto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pashto
Context triple: [Middle Iranian languages, influenced, 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 (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_69c0087361a48190905c6b55969852b8 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f82dd688190ad8882d8fb547cb5 completed March 22, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c108b2f09081908e94f1932aad6e58 completed March 23, 2026, 9:32 a.m.
Created at: March 22, 2026, 4:06 p.m.