Triple
T10852692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DONUT experiment |
E256187
|
entity |
| Predicate | neutrinoFlavorCountConfirmed |
P23070
|
FINISHED |
| Object | three |
—
|
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: three | Statement: [DONUT experiment, neutrinoFlavorCountConfirmed, three]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neutrinoFlavorCountConfirmed Context triple: [DONUT experiment, neutrinoFlavorCountConfirmed, three]
-
A.
measuredNumberOfLightNeutrinoFamilies
chosen
Indicates the experimentally determined count of distinct light neutrino families inferred from measurements.
-
B.
neutrinoFlavorAtSource
Indicates the specific neutrino flavor (e.g., electron, muon, tau) that a neutrino possesses at its point of origin or production.
-
C.
neutrinoDetectionSignificance
Indicates the statistical strength or confidence level that a detected signal is due to neutrinos rather than background noise or random fluctuations.
-
D.
hasQuarkFlavors
Indicates that an entity (such as a particle) possesses specific types (flavors) of quarks as its constituents.
-
E.
leptonNumber
Indicates that a specified lepton number value is assigned to or conserved by a given particle or interaction in a physical process.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75134299481909459fd87917261a7 |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d2b51448190bae748ed6c23edde |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.