Triple
T595018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandown Park Racecourse |
E17360
|
entity |
| Predicate | hasApproximateDistanceFromLondon |
P9423
|
FINISHED |
| Object | about 15 miles south-west of central London |
—
|
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: about 15 miles south-west of central London | Statement: [Sandown Park Racecourse, hasApproximateDistanceFromLondon, about 15 miles south-west of central London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateDistanceFromLondon Context triple: [Sandown Park Racecourse, hasApproximateDistanceFromLondon, about 15 miles south-west of central London]
-
A.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
-
B.
distanceFromCentralLondon
chosen
Indicates the spatial separation or length of travel between a given location and central London.
-
C.
distanceToManchester
Indicates the measured or calculated distance between a given entity’s location and the city of Manchester.
-
D.
distanceToSaintHelena
Indicates the measured distance between a given entity and the location of Saint Helena.
-
E.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd280ac8190b6a530ce73da85c8 |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494ceeb7881909a91ed1a35d5bf0a |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.