Triple

T8990961
Position Surface form Disambiguated ID Type / Status
Subject RUH E214786 entity
Predicate locatedInCity P40 FINISHED
Object Riyadh E7632 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: Riyadh | Statement: [RUH, locatedInCity, Riyadh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riyadh
Context triple: [RUH, locatedInCity, Riyadh]
  • A. Riyadh chosen
    Riyadh is the capital and largest city of Saudi Arabia, serving as a major political, economic, and cultural center in the Arab world.
  • B. Riyad
    Riyad is the given name of Algerian professional footballer Riyad Mahrez, a prominent winger known for his time at Leicester City and Manchester City.
  • C. Dammam
    Dammam is a major Saudi Arabian city and commercial hub on the eastern coast, serving as a key center for the country’s oil industry and maritime trade.
  • D. Jeddah
    Jeddah is a major Saudi Arabian port city on the Red Sea, known as the gateway to the holy cities of Mecca and Medina and a key commercial and cultural hub in the region.
  • E. Diriyah
    Diriyah is a historic town in Saudi Arabia that served as the original home of the Saudi royal family and the capital of the first Saudi state.
  • 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_69ca83a05c608190bdfdbdb25e994b39 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc68733548819096a5ba0ff41e43da completed April 1, 2026, 12:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb92ebf4819092b7ee94af16064b completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:04 p.m.