Triple
T27143878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County Hurdle |
E681887
|
entity |
| Predicate | notableJockeyRecord |
P118174
|
FINISHED |
| Object | Ruby Walsh multiple wins |
—
|
LITERAL 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: Ruby Walsh multiple wins | Statement: [County Hurdle, notableJockeyRecord, Ruby Walsh multiple wins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableJockeyRecord Context triple: [County Hurdle, notableJockeyRecord, Ruby Walsh multiple wins]
-
A.
hasNotableJockey
Indicates that an entity (typically a racehorse) is or was ridden by a jockey who is considered notable or distinguished.
-
B.
notableRacingSuccess
Indicates that the subject has achieved significant or distinguished success in competitive racing events.
-
C.
mostSuccessfulJockey
chosen
Indicates that the subject is the jockey with the highest level of success (e.g., most wins or top performance) in a given context or competition.
-
D.
notableHorse
Indicates that the subject is a horse recognized for particular significance, fame, or distinction.
-
E.
raceRecordWins
Indicates that one entity has achieved a greater number of wins than another entity in recorded races.
- F. None of above.
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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69ff8cecbf048190860b9f72b8753f5c |
completed | May 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69ff8c4c39dc8190b5bf35adc1bae7c6 |
completed | May 9, 2026, 7:34 p.m. |
Created at: April 27, 2026, 9:10 a.m.