Triple
T35924721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PLoS ONE |
E1038987
|
entity |
| Predicate | impactCriterionEmphasis |
P81182
|
FINISHED |
| Object | low |
—
|
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: low | Statement: [PLoS ONE, impactCriterionEmphasis, low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactCriterionEmphasis Context triple: [PLoS ONE, impactCriterionEmphasis, low]
-
A.
impactLevel
Indicates the degree or intensity of effect that one entity, action, or event has on another.
-
B.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
C.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
D.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
-
E.
assessmentEmphasis
chosen
Indicates the particular aspect, component, or criterion of a subject that an assessment is primarily focused on or gives greatest weight to.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.