Triple
T965262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rockwell-MBB X-31 |
E20823
|
entity |
| Predicate | maxAngleOfAttackTested |
P19885
|
FINISHED |
| Object | approximately 70 degrees |
—
|
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: approximately 70 degrees | Statement: [Rockwell-MBB X-31, maxAngleOfAttackTested, approximately 70 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxAngleOfAttackTested Context triple: [Rockwell-MBB X-31, maxAngleOfAttackTested, approximately 70 degrees]
-
A.
wingSweepAngles
Indicates the angular positions of an entity’s wings relative to a reference axis, typically describing how far the wings are swept forward or backward.
-
B.
maximumTakeoffWeight
Indicates the greatest allowable weight an aircraft can have at the start of its takeoff roll under specified conditions.
-
C.
aircraftStrengthPeak
Indicates the maximum strength or capability level that an aircraft reaches during its operational performance.
-
D.
wingArea
Indicates the total surface area covered by an entity’s wing or wings.
-
E.
aerodynamicsFeature
chosen
Indicates that one entity possesses or is characterized by a specific aerodynamic property, component, or design feature affecting airflow and motion through air.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b431d61481908b53490e99670363 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a42c1481908d940cbe0aefdd3b |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.