Triple
T16942785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wayside Inn |
E410987
|
entity |
| Predicate | hasOnsiteFeature |
P125325
|
FINISHED |
| Object | grist mill |
—
|
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: grist mill | Statement: [Wayside Inn, hasOnsiteFeature, grist mill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnsiteFeature Context triple: [Wayside Inn, hasOnsiteFeature, grist mill]
-
A.
hasOnsiteLabel
Indicates that something is physically marked or identified with a label at its location or on its surface.
-
B.
hasOnsiteActivity
Indicates that an entity conducts or participates in activities that physically take place at a specific site or location.
-
C.
hasOnboardFeature
Indicates that an entity includes or is equipped with a particular feature as part of its built-in or onboard capabilities.
-
D.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
-
E.
hasHotelsOnSite
Indicates that the subject location includes one or more hotels situated directly on its premises.
- F. None of above. chosen
Provenance (4 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfafc8448190a25be8ada84eff9c |
completed | April 18, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e355722040819098830dabf207ecd6 |
completed | April 18, 2026, 9:57 a.m. |
Created at: April 10, 2026, 5:31 a.m.