Triple
T21066587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debye unit |
E518988
|
entity |
| Predicate | typicalMolecularScale |
P142715
|
FINISHED |
| Object | order of 1 Debye |
—
|
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: order of 1 Debye | Statement: [Debye unit, typicalMolecularScale, order of 1 Debye]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMolecularScale Context triple: [Debye unit, typicalMolecularScale, order of 1 Debye]
-
A.
microscopicStructure
Indicates the detailed arrangement and organization of components at a microscopic scale within an entity.
-
B.
microscopicMacroscopicLink
Indicates a relationship where microscopic-level phenomena or properties are causally or explanatorily connected to macroscopic-level behavior or observations.
-
C.
hasMacroscopicBehavior
Indicates that an entity exhibits observable large-scale properties or behaviors that emerge from its underlying microscopic components.
-
D.
hasMicroscopicDynamics
Indicates that one entity exhibits or is characterized by underlying microscopic-level behaviors, processes, or interactions that govern its dynamics.
-
E.
typicalSubunitOf
Indicates that something is a standard or commonly occurring subcomponent or part of a larger whole.
- 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_69e0b505ef108190b25dd4033e2ff7eb |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6feb455fc81909cc63fa0e87b6a35 |
completed | April 21, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:45 p.m.