Triple

T16081296
Position Surface form Disambiguated ID Type / Status
Subject Saudi industrial cities program E390115 entity
Predicate includesCity P3207 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: [Saudi industrial cities program, includesCity, Riyadh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riyadh
Context triple: [Saudi industrial cities program, includesCity, 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1844a5c68819086a13c93a787b436 completed April 17, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe48adec081909623355eabee472c completed May 10, 2026, 1:51 a.m.
Created at: April 10, 2026, 4:57 a.m.