Triple
T21901190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wood Memorial Stakes |
E540811
|
entity |
| Predicate | hasNotableWinner |
P2766
|
FINISHED |
| Object | Count Fleet |
—
|
NE NERFINISHED |
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: Count Fleet | Statement: [Wood Memorial Stakes, hasNotableWinner, Count Fleet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Count Fleet Context triple: [Wood Memorial Stakes, hasNotableWinner, Count Fleet]
-
A.
Count Fleet
chosen
Count Fleet was a legendary American Thoroughbred racehorse who dominated in 1943 by winning the U.S. Triple Crown.
-
B.
Battle Fleet
Battle Fleet was the main operational battle group of the United States Fleet in the early 20th century, comprising the Navy’s primary capital ships for major sea engagements.
-
C.
Grand Fleet
The Grand Fleet was the main British Royal Navy battle fleet during World War I, tasked with securing control of the North Sea and confronting the German High Seas Fleet.
-
D.
Fleet
Fleet is a town in Hampshire, England, known for its commuter links to London and surrounding areas.
-
E.
Fleet
Fleet is a publishing imprint of Little, Brown Book Group known for releasing a diverse range of literary and commercial fiction and non-fiction titles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fcb18748190a21071c122b7e6d5 |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:16 p.m.