Triple
T13470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proceedings of the National Academy of Sciences |
E270
|
entity |
| Predicate | subjectAreaCoverage |
P450
|
FINISHED |
| Object | biological sciences |
—
|
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: biological sciences | Statement: [Proceedings of the National Academy of Sciences, subjectAreaCoverage, biological sciences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectAreaCoverage Context triple: [Proceedings of the National Academy of Sciences, subjectAreaCoverage, biological sciences]
-
A.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
B.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
C.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
D.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
researchStrength
Indicates the degree to which an entity possesses strong capabilities, performance, or impact in conducting research.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a243abb2ec8190937365e5ecec52ad |
completed | Feb. 28, 2026, 1:23 a.m. |
| PD | Predicate disambiguation | batch_69a23fe9470c8190918a6ca1df168646 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.