Triple
T22662416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doeschka Meijsing |
E559697
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Elsevier |
—
|
NE NERFINISHED |
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: Elsevier | Statement: [Doeschka Meijsing, employer, Elsevier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elsevier Context triple: [Doeschka Meijsing, employer, Elsevier]
-
A.
Elsevier
chosen
Elsevier is a major Dutch academic publishing company known for producing and distributing scientific, technical, and medical journals, books, and research databases worldwide.
-
B.
Springer Nature
Springer Nature is a major global academic publishing company known for producing high-impact scientific, technical, and medical journals and books.
-
C.
Nature Publishing Group
Nature Publishing Group is a major scientific publishing company best known for producing the prestigious journal Nature and other high-impact research publications across the natural sciences.
-
D.
Wiley-Blackwell
Wiley-Blackwell is a major academic and professional publishing company known for producing scholarly journals and books across a wide range of disciplines.
-
E.
Springer
Springer is a major global academic publishing company known for its extensive catalog of scientific, technical, and medical books and journals.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17660c0c88190bed9fa8f6517eec4 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 3:08 p.m.