Triple
T13567994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devonshire Park Lawn Tennis Club |
E324087
|
entity |
| Predicate | hasCourtSurface |
P110106
|
FINISHED |
| Object | natural grass |
—
|
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: natural grass | Statement: [Devonshire Park Lawn Tennis Club, hasCourtSurface, natural grass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourtSurface Context triple: [Devonshire Park Lawn Tennis Club, hasCourtSurface, natural grass]
-
A.
homeArenaSurface
Indicates the type of playing surface used in an entity’s home arena.
-
B.
homeFieldSurface
Indicates the type of playing surface used at a team's home field or stadium.
-
C.
hasTennisCourt
Indicates that one entity possesses, includes, or provides access to a tennis court as part of its facilities or attributes.
-
D.
hasRaceSurface
Indicates that an event or activity takes place on, or is associated with, a specific type of race surface.
-
E.
outfieldSurface
Indicates the type or condition of the playing surface specifically in the outfield area of a sports field.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00e0188819094fde44f85adb69c |
completed | April 12, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf7fefa881908471f1400f813ccc |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:48 p.m.