Triple
T26752599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaver Creek |
E674580
|
entity |
| Predicate | typeOfAttractions |
P8077
|
FINISHED |
| Object | children’s rides |
—
|
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: children’s rides | Statement: [Beaver Creek, typeOfAttractions, children’s rides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAttractions Context triple: [Beaver Creek, typeOfAttractions, children’s rides]
-
A.
attractionType
chosen
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
-
B.
partOfAttractionType
Indicates that one attraction type is a component or subset of a broader, more general attraction type.
-
C.
ridesAttraction
Indicates that an entity participates in experiencing or using an attraction, such as going on a ride at a venue or amusement location.
-
D.
hasAttractionType
Indicates that one entity is associated with a specific kind or category of attraction (e.g., tourist, cultural, natural).
-
E.
attractionTypeContext
Indicates the specific situational or contextual conditions under which an attraction between entities holds or is characterized.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: April 27, 2026, 3:54 a.m.