Triple
T52733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Palestra |
E1035
|
entity |
| Predicate | hasSurface |
P1242
|
FINISHED |
| Object | hardwood court |
—
|
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: hardwood court | Statement: [The Palestra, hasSurface, hardwood court]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurface Context triple: [The Palestra, hasSurface, hardwood court]
-
A.
hasSurfaceGravity
Indicates that one entity possesses a specific gravitational acceleration at its surface, typically measured as the strength of gravity experienced at or near that surface.
-
B.
surfaceType
chosen
Indicates the kind or classification of surface associated with an entity or interaction.
-
C.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
D.
hasAverageSurfaceSpeed
Indicates the typical or mean speed at which something moves across a surface over a given period or distance.
-
E.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24c709c248190bcd442c8d508e48c |
completed | Feb. 28, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69a24ac3c8dc819099849023bdaa35a9 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.