Triple
T18306870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smuggler’s Cove Beach |
E438507
|
entity |
| Predicate | hasCrowdingLevel |
P18989
|
FINISHED |
| Object | less crowded than other Tortola beaches |
—
|
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: less crowded than other Tortola beaches | Statement: [Smuggler’s Cove Beach, hasCrowdingLevel, less crowded than other Tortola beaches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrowdingLevel Context triple: [Smuggler’s Cove Beach, hasCrowdingLevel, less crowded than other Tortola beaches]
-
A.
hasCrowdLevel
chosen
Indicates the degree or intensity of how crowded a place, event, or situation is.
-
B.
isLessCrowdedThan
Indicates that one place, event, or situation has fewer people present than another for comparison.
-
C.
hasPedestrianTrafficLevel
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
-
D.
hasHeavyPassengerTraffic
Indicates that an entity experiences a high volume of passenger movement or usage over a given period.
-
E.
hasHeavyTraffic
Indicates that a location, route, or area is experiencing a high volume of traffic, causing congestion or delays.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021519a481908a9b6561946f1c65 |
completed | April 19, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.