Triple
T6833417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | gauss |
E157391
|
entity |
| Predicate | conversionToTesla |
P31138
|
FINISHED |
| Object | 1 G = 0.0001 T |
—
|
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: 1 G = 0.0001 T | Statement: [gauss, conversionToTesla, 1 G = 0.0001 T]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conversionToTesla Context triple: [gauss, conversionToTesla, 1 G = 0.0001 T]
-
A.
conversionUse
Indicates that one entity is used as a means, method, or context for converting another entity from one form, state, or representation to another.
-
B.
convertedUnit
chosen
Indicates that one unit is the result of converting a quantity expressed in another unit.
-
C.
inMillinewton
Indicates that a force quantity is measured or expressed in millinewtons (mN).
-
D.
someUnitsConvertedTo
Indicates that a quantity expressed in one unit of measurement has been transformed into an equivalent quantity expressed in another unit.
-
E.
magneticFieldStrength
Indicates the intensity or magnitude of a magnetic field associated with an entity or at a specific location.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d62b1e8c8190a81d91191a54b073 |
completed | March 27, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69c6d09d95f0819091ca7f897dc21efe |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:18 p.m.