Triple
T17713164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EAR2 |
E441620
|
entity |
| Predicate | hasNeutronEnergyRange |
P1457
|
FINISHED |
| Object | from thermal to hundreds of MeV |
—
|
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: from thermal to hundreds of MeV | Statement: [EAR2, hasNeutronEnergyRange, from thermal to hundreds of MeV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeutronEnergyRange Context triple: [EAR2, hasNeutronEnergyRange, from thermal to hundreds of MeV]
-
A.
energyRangeUpperBound_MeV
Indicates the maximum energy value, expressed in mega–electronvolts (MeV), that defines the upper limit of an energy range in the relationship.
-
B.
typicalEnergyRange
chosen
Indicates the usual or characteristic range of energy values associated with an entity, process, or interaction.
-
C.
hasEnergySpectrum
Indicates that one entity possesses or is characterized by a distribution of energy values (an energy spectrum).
-
D.
usesNeutronModerator
Indicates that one entity employs another entity as a neutron moderator to slow down neutrons in a nuclear process or system.
-
E.
neutronSpectrum
Indicates the energy distribution or range of neutrons present in a given system, interaction, or environment.
- 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4729cebd08190872be96a26d0f7ce |
completed | April 19, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:06 a.m.