Triple

T656663
Position Surface form Disambiguated ID Type / Status
Subject Arabian Desert E11663 entity
Predicate country P26 FINISHED
Object Oman E19046 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: Oman | Statement: [Arabian Desert, country, Oman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oman
Context triple: [Arabian Desert, country, Oman]
  • A. Oman chosen
    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.
  • B. 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.
  • C. Qatar
    Qatar is a wealthy Gulf nation on the Arabian Peninsula known for its vast natural gas reserves, rapid modernization, and large expatriate workforce.
  • D. Ras Al Khaimah
    Ras Al Khaimah is one of the seven emirates of the United Arab Emirates, known for its mountains, desert landscapes, and growing tourism industry.
  • E. Yemen
    Yemen is a country on the southern tip of the Arabian Peninsula, known for its ancient history, strategic Red Sea coastline, and ongoing complex humanitarian and political crises.
  • 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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f4e87408190b5276d2b913d0426 completed March 1, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad3ff724248190aacb72d105f0bb34 completed March 8, 2026, 9:23 a.m.
Created at: March 1, 2026, 7:36 p.m.