Triple
T13877892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morne Rouge Bay |
E333628
|
entity |
| Predicate | hasBeachSlope |
P112213
|
FINISHED |
| Object | gentle slope |
—
|
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: gentle slope | Statement: [Morne Rouge Bay, hasBeachSlope, gentle slope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeachSlope Context triple: [Morne Rouge Bay, hasBeachSlope, gentle slope]
-
A.
hasBeach
Indicates that one entity possesses, includes, or is characterized by a beach as part of its features or environment.
-
B.
hasBeachSection
Indicates that an area, location, or property includes or is associated with a specific section designated as a beach.
-
C.
hasBeachNearby
Indicates that one location is situated close enough to another location to have convenient access to a beach.
-
D.
hasSlopeRating
Indicates that something (typically a golf course or hole) is associated with a specific slope rating value that quantifies its relative difficulty for bogey golfers compared to scratch golfers.
-
E.
hasBeachTagRequirement
Indicates that something is subject to a specific requirement or condition related to beach access, use, or tagging.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:15 p.m.