Triple

T9488028
Position Surface form Disambiguated ID Type / Status
Subject Kati language E228811 entity
Predicate hasDialect P4251 FINISHED
Object Kamdeshi E235944 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: Kamdeshi | Statement: [Kati language, hasDialect, Kamdeshi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kamdeshi
Context triple: [Kati language, hasDialect, Kamdeshi]
  • A. Kamdesh area chosen
    The Kamdesh area is a remote mountainous region in eastern Afghanistan’s Nuristan Province, traditionally inhabited by Nuristani communities such as the Kam people.
  • B. Pakhto
    Pakhto is an alternative name for Pashto, an Eastern Iranian language spoken primarily in Afghanistan and Pakistan.
  • C. Khuzdar
    Khuzdar is a major city in central Balochistan that serves as an important regional commercial and administrative center in southwestern Pakistan.
  • D. Pothohari
    Pothohari is a dialect of Punjabi spoken primarily in the Pothohar Plateau region of northern Pakistan.
  • E. Sachal
    Sachal is the honorific name of Sachal Sarmast, an 18th–19th century Sindhi Sufi poet and mystic renowned for his multilingual poetry and message of spiritual unity.
  • 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_69ca847424f081908180305555139f7a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd80c443b88190968d2092a73e1ee4 completed April 1, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d18fd908190b562fa0a8dad7c63 completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:55 p.m.