Triple
T2171484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nobelium |
E48435
|
entity |
| Predicate | radioactivity |
P37366
|
FINISHED |
| Object | highly radioactive |
—
|
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: highly radioactive | Statement: [Nobelium, radioactivity, highly radioactive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: radioactivity Context triple: [Nobelium, radioactivity, highly radioactive]
-
A.
isotopes
Indicates that two or more atomic nuclei are variants of the same chemical element that differ in neutron number (and thus mass number) but share the same number of protons.
-
B.
nuclearMaterial
Indicates that the subject entity is or contains nuclear material, or is directly associated with nuclear substances used for energy, research, or weapons.
-
C.
decayWidth
Indicates the total probability per unit time (or corresponding energy measure) that an unstable particle will decay via all possible channels.
-
D.
numberOfIsotopesProduced
Indicates the quantity of distinct isotopes that are generated or obtained from a specified process, reaction, or source.
-
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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1559ff481908efe3f214b2570dc |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbd9efc1c81909a65044a1ffc9038 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abc153b22481908115e5f582c93f12 |
completed | March 7, 2026, 6:10 a.m. |
Created at: March 4, 2026, 7:45 p.m.