Triple
T139891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IEEE Xplore Digital Library |
E2827
|
entity |
| Predicate | hasCoverage |
P5998
|
FINISHED |
| Object | peer-reviewed literature |
—
|
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: peer-reviewed literature | Statement: [IEEE Xplore Digital Library, hasCoverage, peer-reviewed literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoverage Context triple: [IEEE Xplore Digital Library, hasCoverage, peer-reviewed literature]
-
A.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
hasLandCoverage
Indicates that a specified area or region is covered or occupied by a particular type of land surface or land use.
-
C.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
-
D.
hasSupported
Indicates that one entity has provided assistance, endorsement, or backing to another entity, either materially, emotionally, or through advocacy.
-
E.
hasOceanCoverage
Indicates that a specified area or region is covered by ocean to a certain extent or proportion.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257c679d88190bc71775dab2cfc64 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25737f9188190b9690dce98aed83a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.