Triple

T16510067
Position Surface form Disambiguated ID Type / Status
Subject Multan Division E401036 entity
Predicate hasMajorCity P316 FINISHED
Object Khanewal E445973 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: Khanewal | Statement: [Multan Division, hasMajorCity, Khanewal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khanewal
Context triple: [Multan Division, hasMajorCity, Khanewal]
  • A. Khanewal chosen
    Khanewal is a prominent city in Pakistan’s Punjab province, known as an important railway junction and agricultural trade center.
  • 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. Bahawalnagar
    Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
  • D. 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.
  • E. Sargodha
    Sargodha is a major city in central Pakistan known for its air force base and extensive citrus (particularly kinnow) production.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e54f7508190804bbae4c9bc8fe3 completed April 18, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a014134601c81909f7f4a95d558e067 completed May 11, 2026, 2:38 a.m.
Created at: April 10, 2026, 5:14 a.m.