Triple

T2941390
Position Surface form Disambiguated ID Type / Status
Subject Saraiki people E79392 entity
Predicate majorCityRegion P3940 FINISHED
Object Bahawalpur E224999 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: Bahawalpur | Statement: [Saraiki people, majorCityRegion, Bahawalpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bahawalpur
Context triple: [Saraiki people, majorCityRegion, Bahawalpur]
  • A. Bahawalpur chosen
    Bahawalpur is a historic city in southern Punjab, Pakistan, known for its former princely state status, grand palaces, and proximity to the Cholistan Desert.
  • B. Khairpur
    Khairpur is a historic city in Sindh, Pakistan, known for its former princely state status under the Talpur rulers and its rich cultural and architectural heritage.
  • C. Chakwal
    Chakwal is a city in Pakistan’s Punjab province, known as a regional administrative and commercial center in the Potohar Plateau area.
  • D. Sialkot
    Sialkot is a major industrial city in Pakistan’s Punjab province, renowned globally for its production of sports goods and surgical instruments.
  • E. Multan
    Multan is a historic city in southern Punjab, Pakistan, renowned as a major cultural, commercial, and Sufi spiritual center with a legacy spanning over two millennia.
  • 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_69ad8b1089588190b74d9e2505e45762 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9870e5d08190b3b277ba823fe6a1 completed March 8, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e1d59a48190b06ebe298590feb8 completed March 11, 2026, 8:55 a.m.
Created at: March 8, 2026, 2:56 p.m.