Triple
T33429294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K 51 |
E856079
|
entity |
| Predicate | wingSpanClass |
P4571
|
FINISHED |
| Object | very large wingspan for interwar era |
—
|
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: very large wingspan for interwar era | Statement: [K 51, wingSpanClass, very large wingspan for interwar era]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wingSpanClass Context triple: [K 51, wingSpanClass, very large wingspan for interwar era]
-
A.
wingSpanVariant
Indicates a relationship where one wing span measurement is a variant or alternative form of another wing span measurement.
-
B.
wingLength
Indicates the length or measurement of a wing associated with an entity.
-
C.
wingspan
chosen
Indicates the distance from the tip of one wing to the tip of the other wing when fully extended.
-
D.
wingArea
Indicates the total surface area covered by an entity’s wing or wings.
-
E.
wingConfiguration
Indicates how the wings of an aircraft or creature are arranged or structured relative to its body and to each other.
- 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_69f349709e7881908c342b4d34f555f4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e47f37848190aadb137c81760f1f |
completed | May 3, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:36 a.m.