Triple
T27134882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESCA |
E681654
|
entity |
| Predicate | sensitivityRange |
P12997
|
FINISHED |
| Object | atomic percent level |
—
|
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: atomic percent level | Statement: [ESCA, sensitivityRange, atomic percent level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sensitivityRange Context triple: [ESCA, sensitivityRange, atomic percent level]
-
A.
sensitivityRegion
chosen
Indicates the specific area or domain within which a subject is particularly responsive, vulnerable, or reactive to a given influence or condition.
-
B.
sensitivityFeature
Indicates a relationship where one entity functions as a sensitivity-related characteristic, parameter, or attribute of another entity.
-
C.
coreRange
Indicates the primary spatial or temporal extent within which an entity, phenomenon, or relationship is predominantly present or valid.
-
D.
controlRange
Indicates the spatial or contextual extent within which an entity can exert control or influence over another entity or process.
-
E.
abilityRange
Indicates the spatial or contextual extent within which an entity’s ability, power, or effect can be applied or is valid.
- F. None of above.
Provenance (3 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_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62479bbb88190bcad383443cbd638 |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 9:06 a.m.