Triple

T5508992
Position Surface form Disambiguated ID Type / Status
Subject Jezzar Pasha E144513 entity
Predicate usedMilitarySupportFrom P14966 FINISHED
Object Sidney Smith E75425 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: Sidney Smith | Statement: [Jezzar Pasha, usedMilitarySupportFrom, Sidney Smith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sidney Smith
Context triple: [Jezzar Pasha, usedMilitarySupportFrom, Sidney Smith]
  • A. Sidney Smith
    Sidney Smith was a Canadian politician who served as the country's Secretary of State for External Affairs in the mid-20th century.
  • B. Sidney Smith chosen
    Sidney Smith was a British Royal Navy officer best known for his daring defense of Acre against Napoleon during the French campaign in the Eastern Mediterranean.
  • C. Christopher Smyth
    Christopher Smyth was a 19th-century mountaineer known for making the first recorded ascent of Mont Blanc du Tacul in the Mont Blanc massif of the Alps.
  • D. Christopher Smyth
    Christopher Smyth was one of the mountaineers who achieved the first recorded ascent of Dufourspitze, the highest peak in Switzerland and the Monte Rosa massif.
  • E. Lucian Johnston
    Lucian Johnston is a film editor best known for his work on the acclaimed horror drama "Midsommar."
  • 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_69c008f6b5048190a09064116062cf69 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c021d76e4081908570dc34217c66fe completed March 22, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04cbaca1c8190a7f6d4001f43749c completed March 22, 2026, 8:10 p.m.
Created at: March 22, 2026, 3:33 p.m.