Triple
T1899856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Meteorological Telecommunication Network |
E37666
|
entity |
| Predicate | usesDataType |
P24486
|
FINISHED |
| Object | surface meteorological observations |
—
|
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: surface meteorological observations | Statement: [National Meteorological Telecommunication Network, usesDataType, surface meteorological observations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDataType Context triple: [National Meteorological Telecommunication Network, usesDataType, surface meteorological observations]
-
A.
datumType
Indicates the specific kind or category of data that characterizes or classifies a datum.
-
B.
usesStandardType
Indicates that one entity employs or relies on a predefined, commonly accepted standard type defined elsewhere.
-
C.
usedInType
Indicates that something serves as a component, element, or example within a particular type or category.
-
D.
usesDataStructure
Indicates that one entity employs or relies on a particular data structure in its operation or implementation.
-
E.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
- 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_69a8861be7148190a680937ec451a304 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb18c46c88190b10c05bf5c6a2d9c |
completed | March 7, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69abafe7e7e88190b58c0df59187c0c2 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.