Triple
T4073262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irish grid reference system |
E86697
|
entity |
| Predicate | spatialReferenceScope |
P13939
|
FINISHED |
| Object | national |
—
|
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: national | Statement: [Irish grid reference system, spatialReferenceScope, national]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spatialReferenceScope Context triple: [Irish grid reference system, spatialReferenceScope, national]
-
A.
standardizationScope
Indicates the extent or domain within which a standard or standardization effort is intended to apply or be enforced.
-
B.
identificationScope
Indicates the contextual boundary or extent within which an entity is uniquely identified or recognized.
-
C.
locationScope
chosen
Indicates the specific geographic or spatial area within which a given relationship, condition, or action is considered valid or applicable.
-
D.
scopeType
Indicates the specific range, level, or context within which a given relationship, rule, or action is defined or applies.
-
E.
hasSpatialResolution
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
- 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_69aed93ebe448190a1f1686e28740ac9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc22be988190a2b6575d4f5e0f7b |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.