Triple

T14260432
Position Surface form Disambiguated ID Type / Status
Subject Keifan campus E353498 entity
Predicate country P26 FINISHED
Object Kuwait E14370 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: Kuwait | Statement: [Keifan campus, country, Kuwait]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuwait
Context triple: [Keifan campus, country, Kuwait]
  • A. Kuwait chosen
    Kuwait is a small, oil-rich Gulf nation on the Arabian Peninsula known for its modern capital Kuwait City, significant expatriate workforce, and strategic geopolitical importance.
  • B. Qatar
    Qatar is a wealthy Gulf nation on the Arabian Peninsula known for its vast natural gas reserves, rapid modernization, and large expatriate workforce.
  • C. Bahrain
    Bahrain is a small island nation in the Persian Gulf known for its rich history, oil wealth, and status as a regional financial and cultural hub.
  • D. Bahrain
    Bahrain is a popular riverside town and tourist destination in Pakistan’s Swat Valley, known for its scenic beauty and as a base for exploring nearby mountain areas.
  • E. KSA
    KSA is the IATA airport code for Kosrae International Airport, which serves the island of Kosrae in the Federated States of Micronesia.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de635534988190816fdfb315cd2a3f completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd64789fc88190a3a000e4ee8fe83e completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:09 a.m.