Triple
T19377353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coulomb gap |
E484704
|
entity |
| Predicate | inTwoDimensions |
P95205
|
FINISHED |
| Object | density of states proportional to |E| near Fermi level |
—
|
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: density of states proportional to |E| near Fermi level | Statement: [Coulomb gap, inTwoDimensions, density of states proportional to |E| near Fermi level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inTwoDimensions Context triple: [Coulomb gap, inTwoDimensions, density of states proportional to |E| near Fermi level]
-
A.
in2Dimensions
chosen
Indicates that one entity is located or exists within the two-dimensional spatial extent defined by another entity.
-
B.
plane
Indicates that an entity is a flat, two-dimensional surface extending infinitely in all directions within its dimension.
-
C.
in3Dimensions
Indicates that something exists, occurs, or is represented within three-dimensional space.
-
D.
foundInDimension
Indicates that one entity exists or occurs within a specific dimension associated with another entity.
-
E.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a5cfbf48190ac60e3ffa6baa263 |
completed | April 20, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_69e4fd54f8e48190956e73dd8969164a |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:35 p.m.