Triple
T16644651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albertsons Stadium |
E404434
|
entity |
| Predicate | hasFieldSurface |
P49677
|
FINISHED |
| Object | blue artificial turf |
—
|
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: blue artificial turf | Statement: [Albertsons Stadium, hasFieldSurface, blue artificial turf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFieldSurface Context triple: [Albertsons Stadium, hasFieldSurface, blue artificial turf]
-
A.
hasSurfaceBody
chosen
Indicates that one entity possesses or is characterized by a particular surface or outer body.
-
B.
hasSurfaceSections
Indicates that an entity is composed of or divided into distinct sections or parts of its surface.
-
C.
hasSurfaceLevel
Indicates that one entity possesses or is characterized by a particular degree or measure of surface level (e.g., depth, detail, or superficiality).
-
D.
hasSurfaceFeatureState
Indicates that an entity currently exhibits a particular condition or status of one of its surface features.
-
E.
hasSurfaceForm
Indicates that an abstract concept, entity, or linguistic unit is realized or expressed in a specific textual or lexical form.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad4735c81908a3a227bf02ca489 |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e296af2f88819092c9ffee4a65d7dd |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:18 a.m.