Triple
T11585963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musashi-Koyama Shopping Street Palm |
E274753
|
entity |
| Predicate | isWeatherProtected |
P100449
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Musashi-Koyama Shopping Street Palm, isWeatherProtected, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWeatherProtected Context triple: [Musashi-Koyama Shopping Street Palm, isWeatherProtected, true]
-
A.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
B.
weatherCapability
Indicates that an entity has the ability or functionality to provide, process, or otherwise handle weather-related information or services.
-
C.
canProvideWeatherInformation
Indicates that an entity has the capability to supply or answer queries about weather-related data or conditions.
-
D.
hasMinimumWeatherRequirements
Indicates that a subject is associated with the lowest acceptable set of weather conditions required for a particular activity, operation, or state to occur.
-
E.
weatherConsideration
Indicates that certain conditions, decisions, or actions take into account or are influenced by the current or expected weather.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89462203881908870e991a5b21770 |
completed | April 10, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
| PDg | Predicate description generation | batch_69d87f2e67108190ac36bf47aac12fa8 |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:38 p.m.