Triple
T98756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan NYP monoplane |
E1991
|
entity |
| Predicate | tailConfiguration |
P3547
|
FINISHED |
| Object | conventional tail |
—
|
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: conventional tail | Statement: [Ryan NYP monoplane, tailConfiguration, conventional tail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tailConfiguration Context triple: [Ryan NYP monoplane, tailConfiguration, conventional tail]
-
A.
leafMargin
Indicates the type or pattern of the edge or border of a leaf (e.g., smooth, serrated, lobed).
-
B.
terminus
Indicates that one entity serves as the final endpoint or stopping place for another entity’s movement, route, or process.
-
C.
lineTerminusDirection
Indicates the directional orientation or bearing at which a line segment or route terminates at its endpoint.
-
D.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
E.
trackGauge
Indicates the distance between the inner faces of the rails in a railway track system.
- F. None of above. chosen
Provenance (4 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24ff07d148190a59aee12c807659d |
completed | Feb. 28, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69a24ebe7b1c8190a6bfbf31dc7c7f07 |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a24f4b4658819087902414959161fb |
completed | Feb. 28, 2026, 2:13 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.