Triple
T36978457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pilot Kakuno |
E914758
|
entity |
| Predicate | compatibleConverter |
P192343
|
FINISHED |
| Object | Pilot CON-40 converter |
—
|
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: Pilot CON-40 converter | Statement: [Pilot Kakuno, compatibleConverter, Pilot CON-40 converter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compatibleConverter Context triple: [Pilot Kakuno, compatibleConverter, Pilot CON-40 converter]
-
A.
converter
chosen
Indicates a relationship where one entity transforms, translates, or converts another entity from one form, format, or state into a different one.
-
B.
convertedBy
Indicates that one entity has been transformed or changed in form, state, or representation through the action or process performed by another entity.
-
C.
conversionTarget
Indicates that one entity serves as the intended outcome, goal, or result that another entity is meant to be converted or transformed into.
-
D.
allowsConversionTo
Indicates that one entity permits or enables transformation or change into another specified form or state.
-
E.
conversionContext
Indicates the situational or environmental factors under which a conversion (e.g., change of state, format, or belief) occurs or is interpreted.
- 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_69f76e8d13b4819089af24a47ce092fc |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: May 3, 2026, 4:14 p.m.