Triple
T36493473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington-class aircraft carrier |
E899113
|
entity |
| Predicate | airGroupSizeApproximate |
P4683
|
FINISHED |
| Object | 70–90 aircraft |
—
|
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: 70–90 aircraft | Statement: [Lexington-class aircraft carrier, airGroupSizeApproximate, 70–90 aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airGroupSizeApproximate Context triple: [Lexington-class aircraft carrier, airGroupSizeApproximate, 70–90 aircraft]
-
A.
airGroupSize
chosen
Indicates the number of units or elements grouped together in an air-related context (such as aircraft in a formation or air assets in an operation).
-
B.
typicalGroupSize
Indicates the usual or characteristic number of individuals that typically form a group in this context.
-
C.
sizeOfGroup
Indicates the number of individuals or elements that make up a particular group.
-
D.
airGroupType
Indicates the classification or category of an air group based on its role, composition, or operational function.
-
E.
clubSize
Indicates the number of members or participants in a given club.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.