Triple
T8305952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KETV |
E194462
|
entity |
| Predicate | hasWeatherDepartment |
P82650
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [KETV, hasWeatherDepartment, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWeatherDepartment Context triple: [KETV, hasWeatherDepartment, yes]
-
A.
meteorologicalAgency
Indicates that one entity functions as the official meteorological agency responsible for providing weather and climate services for another entity or region.
-
B.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
C.
hasMeteorologicalStation
Indicates that one entity possesses, hosts, or is equipped with a meteorological station used for observing and recording weather-related data.
-
D.
canProvideWeatherInformation
Indicates that an entity has the capability to supply or answer queries about weather-related data or conditions.
-
E.
cityDepartment
Indicates that one entity is a department that operates within, or is administratively part of, a particular city.
- 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_69ca82e613e88190bf8139669bbd0d53 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f293db08190912e5e8bb7e940cf |
completed | March 31, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69cb70bb3a708190bc705222092da614 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:54 p.m.