Triple
T22941078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boa Viagem Beach |
E569729
|
entity |
| Predicate | hasAverageWaterTemperature |
P9307
|
FINISHED |
| Object | warm year-round |
—
|
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: warm year-round | Statement: [Boa Viagem Beach, hasAverageWaterTemperature, warm year-round]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAverageWaterTemperature Context triple: [Boa Viagem Beach, hasAverageWaterTemperature, warm year-round]
-
A.
hasAverageSummerWaterTemperature
Indicates that an entity is associated with a specific mean water temperature measured over the summer season.
-
B.
waterTemperatureComparedTo
Indicates how the temperature of one body or sample of water compares to the temperature of another.
-
C.
waterTemperatureType
chosen
Indicates the classification or category of a water body’s temperature (e.g., cold, warm, hot) associated with an entity or context.
-
D.
livesInWaterTemperature
Indicates that an entity inhabits or exists in water characterized by a specific temperature or temperature range.
-
E.
waterTemperatureAtSource
Indicates the temperature of water measured at its point of origin or source location.
- 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181394fec81909da791bb346dbd0a |
completed | April 29, 2026, 3:55 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:45 p.m.