Triple
T14302241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brownsville, Oregon |
E354594
|
entity |
| Predicate | hasFilmTourism |
P55845
|
FINISHED |
| Object | visits by fans of "Stand by Me" |
—
|
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: visits by fans of "Stand by Me" | Statement: [Brownsville, Oregon, hasFilmTourism, visits by fans of "Stand by Me"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmTourism Context triple: [Brownsville, Oregon, hasFilmTourism, visits by fans of "Stand by Me"]
-
A.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
B.
hasTourismResource
chosen
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
C.
hasTouristVisits
Indicates that one entity experiences or records visits from tourists to another entity.
-
D.
hasTourismHub
Indicates that a place functions as a central location or focal point for tourism-related activities, services, or attractions for another place or region.
-
E.
hasTour
Indicates that an entity offers, includes, or is associated with a tour experience or guided visit.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717fc2348190bb6ba3109bd2871f |
completed | April 14, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:12 a.m.