Triple
T4898447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward Jenner |
E109738
|
entity |
| Predicate | etymologyOfCoinedTerm |
P453
|
FINISHED |
| Object | vaccine derived from Latin "vacca" meaning cow |
—
|
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: vaccine derived from Latin "vacca" meaning cow | Statement: [Edward Jenner, etymologyOfCoinedTerm, vaccine derived from Latin "vacca" meaning cow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologyOfCoinedTerm Context triple: [Edward Jenner, etymologyOfCoinedTerm, vaccine derived from Latin "vacca" meaning cow]
-
A.
coinedTerm
Indicates that an entity originated and introduced a particular term or expression into use.
-
B.
etymology
chosen
Indicates the historical origin and development of a word or term, including its source language and form.
-
C.
etymologicalSource
Indicates that one term or name originates from, is derived from, or has its roots in another term or name.
-
D.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
-
E.
etymologyReason
Indicates the reason, source, or origin explaining how or why a term acquired its particular etymology.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:28 p.m.