Triple
T1491991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PS |
E29599
|
entity |
| Predicate | accelerationMethod |
P3962
|
FINISHED |
| Object | radio-frequency cavities |
—
|
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: radio-frequency cavities | Statement: [PS, accelerationMethod, radio-frequency cavities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accelerationMethod Context triple: [PS, accelerationMethod, radio-frequency cavities]
-
A.
accelerates
chosen
Indicates that one entity causes an increase in the speed or rate of change of another entity or process.
-
B.
trainingMethod
Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
-
C.
mobilizationMethod
Indicates the method or process by which resources, people, or assets are organized and activated for a particular purpose or operation.
-
D.
tuningMethod
Indicates the method or approach used to adjust or optimize something’s parameters or performance.
-
E.
acceleration0To60mph
Indicates the rate or time it takes for something to increase its speed from 0 to 60 miles per hour.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c4f0c88190a97ba4910c1a5d85 |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c48902808190a8028d359bcf123e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.