Triple
T6054135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Electric F414-GE-100 |
E134865
|
entity |
| Predicate | bypassType |
P67992
|
FINISHED |
| Object | low bypass ratio |
—
|
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: low bypass ratio | Statement: [General Electric F414-GE-100, bypassType, low bypass ratio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bypassType Context triple: [General Electric F414-GE-100, bypassType, low bypass ratio]
-
A.
hasBypass
Indicates that one entity includes or is equipped with an alternative route or mechanism that circumvents or avoids another entity or process.
-
B.
formsBypassOf
Indicates that one entity creates or constitutes an alternative route or channel that circumvents or avoids another entity or process.
-
C.
passType
Indicates the type or category of a pass that is involved in or assigned within the relationship between entities.
-
D.
crossingType
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
E.
tunnelType
Indicates the specific kind or classification of a tunnel associated with an entity.
- 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05708fda48190ad3d1860969ebb6a |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049edc6f0819092ca620d9073ad26 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:09 p.m.