Triple

T10142880
Position Surface form Disambiguated ID Type / Status
Subject Rahim Yar Khan E231628 entity
Predicate majorLanguage P207 FINISHED
Object Seraiki E41867 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: Seraiki | Statement: [Rahim Yar Khan, majorLanguage, Seraiki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seraiki
Context triple: [Rahim Yar Khan, majorLanguage, Seraiki]
  • A. Seraiki chosen
    Seraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
  • B. Gorani
    Gorani is a Northwestern Iranian language variety traditionally spoken by Kurdish communities in parts of Iran and Iraq, notable for its rich literary and religious heritage.
  • C. Siwi
    Siwi is a Berber language spoken primarily in Egypt’s Siwa Oasis, known for its unique features and relative isolation from other Berber varieties.
  • D. Kurmanji
    Kurmanji is the most widely spoken dialect of the Kurdish language, used primarily by Kurds across Turkey, Syria, Iraq, Iran, and the diaspora.
  • E. Siwi language
    The Siwi language is a Berber (Amazigh) language spoken by the Siwi people in Egypt’s Siwa Oasis, characterized by significant Arabic influence and its status as one of the easternmost Berber languages.
  • 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_69ca848364f881908a24366a6feec1db completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdeb273fec8190818707167e031d58 completed April 2, 2026, 4:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e60e51488190a6097837eb3ce18a completed April 5, 2026, 10:45 p.m.
Created at: March 30, 2026, 9:07 p.m.