Triple
T662082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Hall (Hockey Hall of Fame) |
E11776
|
entity |
| Predicate | hasDecorativeFeature |
P6684
|
FINISHED |
| Object | stained glass windows |
—
|
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: stained glass windows | Statement: [Great Hall (Hockey Hall of Fame), hasDecorativeFeature, stained glass windows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDecorativeFeature Context triple: [Great Hall (Hockey Hall of Fame), hasDecorativeFeature, stained glass windows]
-
A.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
B.
isWearableDecoration
Indicates that one entity serves as a decorative item intended to be worn on the body by another entity.
-
C.
hasArchitecturalFeature
chosen
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
-
D.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
E.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fd081e8819097f289961f5eff29 |
completed | March 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69a49d153a948190b3ccdc331ed33617 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.