Triple
T592330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyannisport Club |
E17302
|
entity |
| Predicate | windConditions |
P2125
|
FINISHED |
| Object | frequent coastal winds |
—
|
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: frequent coastal winds | Statement: [Hyannisport Club, windConditions, frequent coastal winds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: windConditions Context triple: [Hyannisport Club, windConditions, frequent coastal winds]
-
A.
weatherCondition
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
B.
prevailingSurfaceWinds
chosen
Indicates the typical or most frequently occurring wind direction and speed that dominate at a given location over a specified period.
-
C.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
D.
winterCharacteristic
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
E.
environmentalCondition
Indicates the state or characteristics of the surrounding physical environment that affect or describe a situation, process, or entity.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bbaf53081908eed240bed09f63b |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cd7d3c8190af008acf34a2293b |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.