Triple
T28051005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunn diode |
E708818
|
entity |
| Predicate | requiresBiasType |
P190658
|
FINISHED |
| Object | DC bias |
—
|
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: DC bias | Statement: [Gunn diode, requiresBiasType, DC bias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresBiasType Context triple: [Gunn diode, requiresBiasType, DC bias]
-
A.
requiresBiasVoltage
Indicates that one entity must have a specific bias voltage applied in order for the other entity or process to operate correctly or as intended.
-
B.
basisType
Indicates the type or category of foundational support or underlying structure on which something is based.
-
C.
requiresFeatureScaling
Indicates that applying feature scaling is a necessary preprocessing step for the associated data or model.
-
D.
supportsRegionBiasing
Indicates that the subject is capable of applying or honoring region-specific preferences or priorities in its behavior or processing.
-
E.
requiresDisplayType
Indicates that one entity can only be properly used, rendered, or interpreted when a specific type of display or presentation format is available.
- 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_69ef9b6df9f48190bbb971d02cbe1b65 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fcce2cf9188190b3f65b362203a6a3 |
completed | May 7, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fccdd2d84481909a7ce22407def9c7 |
completed | May 7, 2026, 5:37 p.m. |
Created at: April 27, 2026, 8:33 p.m.