Triple
T10671415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bacoor Bay |
E251496
|
entity |
| Predicate | experiencesWeather |
P2044
|
FINISHED |
| Object | southwest monsoon |
—
|
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: southwest monsoon | Statement: [Bacoor Bay, experiencesWeather, southwest monsoon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: experiencesWeather Context triple: [Bacoor Bay, experiencesWeather, southwest monsoon]
-
A.
hasWeather
chosen
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
B.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
C.
climateBetween
Indicates that something (such as a location, period, or condition) has a climate that lies within a specified range or intermediate state between two other climatic conditions.
-
D.
weatherCapability
Indicates that an entity has the ability or functionality to provide, process, or otherwise handle weather-related information or services.
-
E.
weatherCondition
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6f8648a248190a3bd284c569152e4 |
completed | April 9, 2026, 12:52 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8a93208190a573061387e2aebb |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:09 p.m.