Triple

T11837671
Position Surface form Disambiguated ID Type / Status
Subject Punjab (Pakistan) E281559 entity
Predicate hasMajorCity P316 FINISHED
Object Sargodha E606500 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: Sargodha | Statement: [Punjab (Pakistan), hasMajorCity, Sargodha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sargodha
Context triple: [Punjab (Pakistan), hasMajorCity, Sargodha]
  • A. Sargodha chosen
    Sargodha is a major city in central Pakistan known for its air force base and extensive citrus (particularly kinnow) production.
  • B. Chakwal
    Chakwal is a city in Pakistan’s Punjab province, known as a regional administrative and commercial center in the Potohar Plateau area.
  • C. Bahawalpur
    Bahawalpur is a historic city in southern Punjab, Pakistan, known for its former princely state status, grand palaces, and proximity to the Cholistan Desert.
  • D. Khanewal
    Khanewal is a prominent city in Pakistan’s Punjab province, known as an important railway junction and agricultural trade center.
  • E. Bahawalnagar
    Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
  • 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a62fec0881908c7b89c0b5bcc9a2 completed April 10, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6366adc8190b5c8163af684afde completed May 2, 2026, 1:03 p.m.
Created at: April 8, 2026, 9:43 p.m.