Triple
T28546888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodgers Beach |
E722466
|
entity |
| Predicate | popularityComparedToOtherBeachesInAruba |
P147983
|
FINISHED |
| Object | less crowded |
—
|
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 | Statement: [Rodgers Beach, popularityComparedToOtherBeachesInAruba, less crowded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularityComparedToOtherBeachesInAruba Context triple: [Rodgers Beach, popularityComparedToOtherBeachesInAruba, less crowded]
-
A.
popularityComparedToWhiteBeach
Indicates how the popularity of one entity compares relative to that of White Beach.
-
B.
ArubaStatus
Indicates the operational or condition state associated with Aruba (such as a device, service, or system) at a given time.
-
C.
relativeToOtherBeaches
chosen
Indicates a comparative relationship that expresses how one beach is characterized or evaluated in relation to other beaches.
-
D.
famousBeach
Indicates that a beach is widely known and recognized, typically for its popularity, beauty, or cultural significance.
-
E.
discoveredAsSurfSpotBy
Indicates that a location became recognized and used as a surf spot through the actions or discovery of a particular person or group.
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 28, 2026, 3:39 a.m.