Triple
T18319092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Buick |
E438821
|
entity |
| Predicate | hasRidden |
P98191
|
FINISHED |
| Object | top-level Godolphin horses |
—
|
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: top-level Godolphin horses | Statement: [William Buick, hasRidden, top-level Godolphin horses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRidden Context triple: [William Buick, hasRidden, top-level Godolphin horses]
-
A.
hasRideExperience
chosen
Indicates that one entity has undergone, participated in, or possesses experience with a particular ride or riding activity in relation to another entity.
-
B.
hasNotableRide
Indicates that an entity is associated with a particularly remarkable or well-known ride or attraction.
-
C.
isFlownOn
Indicates that an entity (such as a person or object) travels or is transported using a particular aircraft or airline as the means of flight.
-
D.
hasHad
Indicates that an entity previously experienced, possessed, or was involved in something at some point in the past.
-
E.
hasTourHistoryWith
Indicates that two entities have previously participated together in one or more tours or touring events.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aa4d3308190883714e1ef6a1d84 |
completed | April 19, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.