Triple
T309850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larry O’Brien Championship Trophy |
E6380
|
entity |
| Predicate | designFeatures |
P7153
|
FINISHED |
| Object | basketball tilted at a 23.5-degree angle |
—
|
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: basketball tilted at a 23.5-degree angle | Statement: [Larry O’Brien Championship Trophy, designFeatures, basketball tilted at a 23.5-degree angle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designFeatures Context triple: [Larry O’Brien Championship Trophy, designFeatures, basketball tilted at a 23.5-degree angle]
-
A.
designUse
Indicates that one entity is used as a design basis, purpose, or intended functional use for another entity.
-
B.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
C.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
D.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
E.
keyFeature
chosen
Indicates that something is a primary, distinguishing, or most important feature of an entity.
- 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_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea33ba688190b30d285cd7aa0d82 |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93f38308190b4b480c951f1a1c3 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.