Triple
T25269881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vatses Beach |
E633537
|
entity |
| Predicate | attractsTypeOfVisitor |
P158435
|
FINISHED |
| Object | visitors avoiding mass tourism |
—
|
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: visitors avoiding mass tourism | Statement: [Vatses Beach, attractsTypeOfVisitor, visitors avoiding mass tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attractsTypeOfVisitor Context triple: [Vatses Beach, attractsTypeOfVisitor, visitors avoiding mass tourism]
-
A.
attractionType
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
-
B.
attractsAgeGroup
Indicates that something tends to draw interest or appeal from people belonging to a particular age group.
-
C.
attractionBasedOn
Indicates a relationship where one entity is drawn to or interested in another specifically because of certain attributes, qualities, or characteristics that the latter possesses.
-
D.
alsoAttractsTouristsIn
Indicates that a place, in addition to another, draws or appeals to tourists within a specified location or context.
-
E.
isMajorAttractionFor
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
- 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_69e75a92f48881909974ff9c11150a2e |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48ba023b481908b6c6caf212818a3 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f4683472ec8190a483b3b8afe71720 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 1:16 p.m.