Triple
T16203417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | californium-252 |
E393260
|
entity |
| Predicate | neutronEmissionRate |
P122144
|
FINISHED |
| Object | about 2.3×10^12 neutrons per second per gram |
—
|
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: about 2.3×10^12 neutrons per second per gram | Statement: [californium-252, neutronEmissionRate, about 2.3×10^12 neutrons per second per gram]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neutronEmissionRate Context triple: [californium-252, neutronEmissionRate, about 2.3×10^12 neutrons per second per gram]
-
A.
neutronSpectrum
Indicates the energy distribution or range of neutrons present in a given system, interaction, or environment.
-
B.
neutronFluxType
Indicates the specific classification or category of neutron flux characterizing how neutrons are distributed or behave in a given context.
-
C.
neutronDetectionReaction
Indicates a reaction in which neutrons are detected through their interaction with a target or detector material.
-
D.
usesNeutronModerator
Indicates that one entity employs another entity as a neutron moderator to slow down neutrons in a nuclear process or system.
-
E.
thermalNeutronCaptureCrossSection
Indicates the probability that a nucleus will capture a thermal (low-energy) neutron, expressed as an effective interaction cross-sectional area.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2270ca18c8190a259992aed4ec072 |
completed | April 17, 2026, 12:26 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:03 a.m.