Triple
T210316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Born–Huang expansion |
E4701
|
entity |
| Predicate | wavefunctionType |
P9139
|
FINISHED |
| Object | total electron–nuclear wavefunction |
—
|
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: total electron–nuclear wavefunction | Statement: [Born–Huang expansion, wavefunctionType, total electron–nuclear wavefunction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wavefunctionType Context triple: [Born–Huang expansion, wavefunctionType, total electron–nuclear wavefunction]
-
A.
beamType
Indicates the specific kind or category of beam involved in the relationship or action.
-
B.
kernelType
Indicates the specific kind or category of kernel associated with or used by an entity.
-
C.
solutionType
Indicates the specific category or kind of solution associated with an entity or problem.
-
D.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
E.
variant
Indicates that one entity is an alternative form, version, or variation of another entity.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25d3463648190ac716d7475378536 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.