Triple

T8157858
Position Surface form Disambiguated ID Type / Status
Subject Vehari Campus E190497 entity
Predicate city P40 FINISHED
Object Vehari E769817 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: Vehari | Statement: [Vehari Campus, city, Vehari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vehari
Context triple: [Vehari Campus, city, Vehari]
  • A. Vehari chosen
    Vehari is a city in the Punjab province of Pakistan, known as an agricultural and educational hub in the region.
  • B. Attock
    Attock is a historic city in northern Pakistan strategically located along the Indus River, long serving as a key gateway between the Punjab region and Khyber Pakhtunkhwa.
  • 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. 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.
  • E. 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.
  • 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb44da14a481909f8d3277762b0e75 completed March 31, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd05abe248190a2dc2dbb27255a87 completed April 3, 2026, 2:36 p.m.
Created at: March 30, 2026, 5:37 p.m.