Triple
T26032659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raccoon Mario |
E647474
|
entity |
| Predicate | canTakeOff |
P14512
|
FINISHED |
| Object | After running to build speed |
—
|
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: After running to build speed | Statement: [Raccoon Mario, canTakeOff, After running to build speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canTakeOff Context triple: [Raccoon Mario, canTakeOff, After running to build speed]
-
A.
hasTakeoffAndLandingCapability
Indicates that an entity possesses the ability to both take off and land, typically under its own operational power or design.
-
B.
landingCapability
Indicates the ability or suitability of an entity (e.g., a vehicle or system) to perform a landing under specified conditions.
-
C.
takeoffCharacteristic
Indicates the specific properties or conditions associated with how an entity takes off, such as its manner, performance, or requirements during takeoff.
-
D.
takeoffMethod
chosen
Indicates the method or procedure by which an aircraft or object initiates its takeoff from a surface or launch point.
-
E.
hasLandingConditions
Indicates the specific conditions or requirements that must be met for a landing to occur or be permitted.
- 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_69e77e8b60e88190a3b26c4f0032a2c2 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6061b1b5081908dc5e2ac3ac58619 |
completed | May 2, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f5aff889988190ad10bcf1a280f717 |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 22, 2026, 9:06 a.m.