Triple
T18815877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | beryllium |
E460131
|
entity |
| Predicate | thermalNeutronModerator |
P133534
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [beryllium, thermalNeutronModerator, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thermalNeutronModerator Context triple: [beryllium, thermalNeutronModerator, true]
-
A.
usesNeutronModerator
Indicates that one entity employs another entity as a neutron moderator to slow down neutrons in a nuclear process or system.
-
B.
thermalNeutronReactor
Indicates that the subject is a nuclear reactor that operates using thermal (low-energy) neutrons to sustain its fission chain reaction.
-
C.
controlRodMaterial
Indicates the material from which a control rod is made in a nuclear or control system context.
-
D.
thermalNeutronCaptureCrossSection
Indicates the probability that a nucleus will capture a thermal (low-energy) neutron, expressed as an effective interaction cross-sectional area.
-
E.
nuclearMaterial
Indicates that the subject entity is or contains nuclear material, or is directly associated with nuclear substances used for energy, research, or weapons.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3e092e081908fc310c70f646e79 |
completed | April 20, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:53 a.m.