Triple

T67165
Position Surface form Disambiguated ID Type / Status
Subject Arab world E1339 entity
Predicate hasCountry P846 FINISHED
Object Bahrain E18452 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: Bahrain | Statement: [Arab world, hasCountry, Bahrain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bahrain
Context triple: [Arab world, hasCountry, Bahrain]
  • A. Bahrain chosen
    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.
  • 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. Oman
    Oman is a Middle Eastern country on the southeastern coast of the Arabian Peninsula, known for its historic trading ports, desert and mountain landscapes, and stable, oil-based economy.
  • D. Kuwait
    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.
  • E. United Arab Emirates
    The United Arab Emirates is a wealthy Gulf nation on the Arabian Peninsula known for its rapid modernization, iconic cities like Dubai and Abu Dhabi, and its large expatriate workforce.
  • 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_69a24ba4f760819081f6638a3c70538a completed Feb. 28, 2026, 1:57 a.m.
NER Named-entity recognition batch_69a24f01a2108190a494e7bfcced8290 completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2e0f1571481908459c38b1e949b3f completed Feb. 28, 2026, 12:34 p.m.
Created at: Feb. 28, 2026, 2:02 a.m.