Triple
T8204546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Global Data-processing Centres |
E191656
|
entity |
| Predicate | handlesDataType |
P79338
|
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: [Global Data-processing Centres, handlesDataType, surface meteorological observations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: handlesDataType Context triple: [Global Data-processing Centres, handlesDataType, surface meteorological observations]
-
A.
appliesToDataType
chosen
Indicates that a rule, operation, or construct is specifically intended to be used with, or is valid for, a particular data type.
-
B.
analyzesDataType
Indicates that one entity examines, interprets, or evaluates a particular type or category of data.
-
C.
dataTypes
Indicates that one entity specifies or defines the kinds or formats of data that are valid or expected for another entity.
-
D.
hasHandleType
Indicates that one entity possesses or is characterized by a specific type or style of handle.
-
E.
hasLinguisticDataType
Indicates that something is associated with or characterized by a specific type or category of linguistic data.
- 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb7268e2dc8190b630ea2bb75d0474 |
completed | March 31, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_69cb36ad01ac81909609b15f6a6c8581 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:43 p.m.