Triple
T19450047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OS National Grid |
E486591
|
entity |
| Predicate | typicalPrecisionLevels |
P109501
|
FINISHED |
| Object | 1 km grid reference |
—
|
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: 1 km grid reference | Statement: [OS National Grid, typicalPrecisionLevels, 1 km grid reference]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPrecisionLevels Context triple: [OS National Grid, typicalPrecisionLevels, 1 km grid reference]
-
A.
supportsPrecisionLevels
Indicates that one entity is capable of operating at, or accommodating, multiple specified levels of precision in relation to another entity or process.
-
B.
typicalHorizontalAccuracy
Indicates the usual or expected degree of precision in the horizontal (x–y) position of a measurement or location estimate.
-
C.
granularityLevel
chosen
Indicates the degree of detail or resolution at which something is specified, measured, or analyzed within a given context.
-
D.
measurementLevel
Indicates the degree or scale at which something is measured or quantified, such as its level, intensity, or magnitude.
-
E.
typicalHighestLevel
Indicates the usual or most common maximum level or degree that something typically reaches within a given context.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338caeb48190aeb1d511996984e3 |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.