Triple
T27868581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lou's Cafe |
E704427
|
entity |
| Predicate | hasOnScreenFeatures |
P125325
|
FINISHED |
| Object | counter with stools |
—
|
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: counter with stools | Statement: [Lou's Cafe, hasOnScreenFeatures, counter with stools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenFeatures Context triple: [Lou's Cafe, hasOnScreenFeatures, counter with stools]
-
A.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
-
B.
hasOnscreenFunction
Indicates that an entity serves a particular role or performs a specific function when it appears on screen.
-
C.
hasOnboardFeature
Indicates that an entity includes or is equipped with a particular feature as part of its built-in or onboard capabilities.
-
D.
hasOnsiteFeature
chosen
Indicates that one entity possesses or includes a particular feature that is physically present at its location or premises.
-
E.
hasOnScreenDynamic
Indicates that one entity displays or presents another entity as a changing or interactive element on a screen.
- 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_69ef840f12408190b539d00d79658abf |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 6:22 p.m.