Triple

T11837668
Position Surface form Disambiguated ID Type / Status
Subject Punjab (Pakistan) E281559 entity
Predicate hasMajorCity P316 FINISHED
Object Gujranwala E68483 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: Gujranwala | Statement: [Punjab (Pakistan), hasMajorCity, Gujranwala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gujranwala
Context triple: [Punjab (Pakistan), hasMajorCity, Gujranwala]
  • A. Gujranwala chosen
    Gujranwala is a major industrial city in Pakistan’s Punjab province, known for its manufacturing base and historical significance in the region.
  • B. Jhang
    Jhang is a historic city in the Punjab province of Pakistan, known for its cultural heritage and as the birthplace of several notable figures.
  • C. Khanewal
    Khanewal is a prominent city in Pakistan’s Punjab province, known as an important railway junction and agricultural trade center.
  • D. Rahim Yar Khan
    Rahim Yar Khan is a major city in southern Punjab, Pakistan, known as an important commercial and agricultural center in the Seraiki-speaking region.
  • E. Vehari
    Vehari is a city in the Punjab province of Pakistan, known as an agricultural and educational hub in the 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_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_69f41787c08c8190a3427aaf2f639889 completed May 1, 2026, 3:01 a.m.
Created at: April 8, 2026, 9:43 p.m.