Triple
T17770841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of Wales's Stakes |
E443631
|
entity |
| Predicate | approximateFurlongs |
P50584
|
FINISHED |
| Object | 10 furlongs |
—
|
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: 10 furlongs | Statement: [Prince of Wales's Stakes, approximateFurlongs, 10 furlongs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateFurlongs Context triple: [Prince of Wales's Stakes, approximateFurlongs, 10 furlongs]
-
A.
approximateDistanceFurlongs
chosen
Indicates an estimated or not-exact distance between entities, measured in furlongs.
-
B.
approximateLengthInMiles
Indicates the estimated distance or extent of something measured in miles.
-
C.
inImperialSystemApprox
Indicates that a quantity is approximately expressed or measured in the imperial system of units rather than exactly or in another unit system.
-
D.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
E.
approximateRouteLength
Indicates the estimated total distance or length of a given route, rather than its exact measured value.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485ff928481909fe32260ba57978f |
completed | April 19, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:11 a.m.