Triple
T36358545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Ministry Specification B.9/32 |
E895417
|
entity |
| Predicate | yearCodeMeaning |
P145061
|
FINISHED |
| Object | 32 indicates year 1932 |
—
|
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: 32 indicates year 1932 | Statement: [Air Ministry Specification B.9/32, yearCodeMeaning, 32 indicates year 1932]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearCodeMeaning Context triple: [Air Ministry Specification B.9/32, yearCodeMeaning, 32 indicates year 1932]
-
A.
digitMeaning
Indicates that a particular digit symbol is associated with a specific numerical value or conceptual meaning.
-
B.
yearType
Indicates the classification or category assigned to a specific year (e.g., academic, fiscal, calendar, leap).
-
C.
yearCirca
Indicates that the associated year is approximate or uncertain rather than exact.
-
D.
codeNumberMeaning
chosen
Indicates that a specific code number is associated with and represents a particular meaning or interpretation.
-
E.
yearDescribedAs
Indicates the specific year in which something was formally characterized, documented, or described.
- 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_69f76e5044248190b390d8887dc03254 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb3ff1b08190802b1063d55d3923 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a611a081908dd6aec1df3f4d7f |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.