Triple
T21283223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seger Beach |
E524583
|
entity |
| Predicate | relativeCrowdedness |
P81846
|
FINISHED |
| Object | less crowded than other Lombok 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 Lombok beaches | Statement: [Seger Beach, relativeCrowdedness, less crowded than other Lombok beaches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeCrowdedness Context triple: [Seger Beach, relativeCrowdedness, less crowded than other Lombok beaches]
-
A.
isLessCrowdedThan
chosen
Indicates that one place, event, or situation has fewer people present than another for comparison.
-
B.
hasCrowdLevel
Indicates the degree or intensity of how crowded a place, event, or situation is.
-
C.
relativeTrafficLevel
Indicates the comparative intensity or volume of traffic between two or more locations, routes, or time periods.
-
D.
relativePopulation
Indicates the comparative size of one population relative to another, typically expressing how large, small, or proportionate it is.
-
E.
hasApproximateNumberOfPeople
Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d3dfbc819081bd876d95c7c480 |
completed | April 21, 2026, 8:35 a.m. |
| PD | Predicate disambiguation | batch_69e61612ab748190a72b8703b938abcb |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 4:03 p.m.