Triple
T4642771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Churchill Downs |
E101692
|
entity |
| Predicate | turfCourseDistance |
P57551
|
FINISHED |
| Object | 0.875 mile |
—
|
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: 0.875 mile | Statement: [Churchill Downs, turfCourseDistance, 0.875 mile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turfCourseDistance Context triple: [Churchill Downs, turfCourseDistance, 0.875 mile]
-
A.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
B.
hasYardage
Indicates that something possesses or is associated with a specific measured distance or length, typically expressed in yards.
-
C.
raceDistanceType
Indicates the specific type or category of distance over which a race is conducted.
-
D.
approximateRoundTripDistanceFromTrailhead
Indicates the estimated total distance of a complete out-and-back journey measured from the trailhead.
-
E.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
- F. None of above. chosen
Provenance (4 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a93047c8190990c94fd5a57c867 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5234d24c819095c79890b70eff9a |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:14 p.m.