Triple
T36803288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | thorium |
E909377
|
entity |
| Predicate | neutronCapture |
P186311
|
FINISHED |
| Object | fertile |
—
|
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: fertile | Statement: [thorium, neutronCapture, fertile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neutronCapture Context triple: [thorium, neutronCapture, fertile]
-
A.
neutronCaptureProduct
Indicates the nuclide that results from a neutron capture reaction involving a given target nucleus.
-
B.
thermalNeutronCaptureCrossSection
Indicates the probability that a nucleus will capture a thermal (low-energy) neutron, expressed as an effective interaction cross-sectional area.
-
C.
neutronDetectionReaction
Indicates a reaction in which neutrons are detected through their interaction with a target or detector material.
-
D.
neutronEmissionRate
Indicates the rate at which neutrons are emitted from a source or system over a given period of time.
-
E.
thermalNeutronReactor
Indicates that the subject is a nuclear reactor that operates using thermal (low-energy) neutrons to sustain its fission chain reaction.
- 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_69f76e7b98888190899b6478a82ad6ae |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7cabdd2d88190be1c8de7e499cb83 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c89b528c8190bf80b230fc7c7108 |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7ca91f1808190b2a05c4b691da0bb |
completed | May 3, 2026, 10:22 p.m. |
Created at: May 3, 2026, 4:12 p.m.