Triple
T5014827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British National Grid |
E112713
|
entity |
| Predicate | supportsPrecisionLevels |
P60855
|
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: [British National Grid, supportsPrecisionLevels, 1 km grid reference]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPrecisionLevels Context triple: [British National Grid, supportsPrecisionLevels, 1 km grid reference]
-
A.
usesConformanceLevels
Indicates that one entity applies or adheres to defined conformance levels when interacting with or evaluating another entity.
-
B.
supersededInPrecisionBy
Indicates that one entity’s level of precision has been replaced or overtaken by another entity’s greater precision.
-
C.
accuracyDependsOn
Indicates that the accuracy of one entity or process is contingent upon, or influenced by, another entity or factor.
-
D.
hasSurfaceAccuracy
Indicates that one entity possesses a specified degree or measure of accuracy related to its surface characteristics or representation.
-
E.
representationLevel
Indicates the degree or layer at which something stands in for, models, or symbolizes something else (e.g., more concrete vs. more abstract representation).
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd732e0b848190858407920e7aefd0 |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd73089f548190834103366e24ab40 |
completed | March 20, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:35 p.m.