Triple
T7188699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sievert |
E167632
|
entity |
| Predicate | equalsInAbsorbedDoseTo |
P75647
|
FINISHED |
| Object | gray for weighting factor 1 |
—
|
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: gray for weighting factor 1 | Statement: [sievert, equalsInAbsorbedDoseTo, gray for weighting factor 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equalsInAbsorbedDoseTo Context triple: [sievert, equalsInAbsorbedDoseTo, gray for weighting factor 1]
-
A.
radiationToleranceTotalIonizingDose
Indicates the maximum total ionizing radiation dose an entity can withstand before its performance or integrity is adversely affected.
-
B.
ionizingSource
Indicates that the subject acts as a source that produces or emits ionizing radiation affecting the object.
-
C.
usedRadioisotope
Indicates that one entity employed or applied a specific radioisotope in an action, process, or context involving another entity.
-
D.
valueSI
Indicates that an entity has a quantitative value expressed in SI (International System of Units) units.
-
E.
beamEnergyUnit
Indicates the unit of measurement used to express the energy of a beam.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8e3d9188190ba2792098d76fb86 |
completed | March 27, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e8b5f6508190af28e06a7959d717 |
completed | March 27, 2026, 8:29 p.m. |
Created at: March 27, 2026, 2:50 p.m.