Triple
T22182578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wright Glider (1902) |
E548206
|
entity |
| Predicate | hasApproximateWingArea |
P18769
|
FINISHED |
| Object | 305 sq ft |
—
|
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: 305 sq ft | Statement: [Wright Glider (1902), hasApproximateWingArea, 305 sq ft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateWingArea Context triple: [Wright Glider (1902), hasApproximateWingArea, 305 sq ft]
-
A.
wingArea
chosen
Indicates the total surface area covered by an entity’s wing or wings.
-
B.
wingSpanVariant
Indicates a relationship where one wing span measurement is a variant or alternative form of another wing span measurement.
-
C.
isFixedWing
Indicates that the subject is an aircraft that uses fixed, non-flapping wings to generate lift rather than rotating or flapping components.
-
D.
hasWingConfiguration
Indicates how an entity’s wings are arranged, structured, or configured relative to its body or to each other.
-
E.
airWingType
Indicates the classification or category of an air wing associated with an entity.
- 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_69e11e3d53f88190a2b690e3f25bb062 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aa687808190b9959d4e91db948a |
completed | April 28, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:35 p.m.