Triple
T5588253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kempton Park Racecourse |
E146808
|
entity |
| Predicate | hasAllWeatherTrack |
P3284
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kempton Park Racecourse, hasAllWeatherTrack, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAllWeatherTrack Context triple: [Kempton Park Racecourse, hasAllWeatherTrack, yes]
-
A.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
B.
hasMinimumWeatherRequirements
Indicates that a subject is associated with the lowest acceptable set of weather conditions required for a particular activity, operation, or state to occur.
-
C.
hasWeatherMinimums
Indicates that there are specified minimum weather conditions that must be met for a particular activity, operation, or status to be allowed.
-
D.
hasTrack
chosen
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
E.
hasWindPattern
Indicates that one entity exhibits, is characterized by, or is associated with a particular pattern of wind behavior.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0209e892c8190b936a05ef2a14d36 |
completed | March 22, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.