Triple
T768560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silver |
E16227
|
entity |
| Predicate | thermalNeutronCaptureCrossSection |
P19732
|
FINISHED |
| Object | high compared to many metals |
—
|
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: high compared to many metals | Statement: [Silver, thermalNeutronCaptureCrossSection, high compared to many metals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thermalNeutronCaptureCrossSection Context triple: [Silver, thermalNeutronCaptureCrossSection, high compared to many metals]
-
A.
neutronSpectrum
Indicates the energy distribution or range of neutrons present in a given system, interaction, or environment.
-
B.
hasNeutronNumber
Indicates that an entity (typically an atom or nuclide) has a specified number of neutrons in its nucleus.
-
C.
nuclearMaterial
Indicates that the subject entity is or contains nuclear material, or is directly associated with nuclear substances used for energy, research, or weapons.
-
D.
isNucleusOfIsotope
Indicates that a given nucleus belongs to and characterizes a specific isotope.
-
E.
numberOfIsotopesProduced
Indicates the quantity of distinct isotopes that are generated or obtained from a specified process, reaction, or source.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a765ba688190ab328bb159583077 |
completed | March 1, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69a4a5074c788190a74fc20ad24e2d26 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a7648a6c8190a9051a3d177ff7e2 |
completed | March 1, 2026, 8:53 p.m. |
Created at: March 1, 2026, 7:37 p.m.