Triple
T17579783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvano |
E428169
|
entity |
| Predicate | etymologicalMeaningComponent |
P53707
|
FINISHED |
| Object | silva (Latin for forest) |
—
|
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: silva (Latin for forest) | Statement: [Silvano, etymologicalMeaningComponent, silva (Latin for forest)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologicalMeaningComponent Context triple: [Silvano, etymologicalMeaningComponent, silva (Latin for forest)]
-
A.
etymologicalRootMeaning
Indicates that one term’s meaning originates from or is derived from the historical or original meaning of another term.
-
B.
etymologicalField
Indicates that one term belongs to a particular semantic or conceptual domain relevant to its etymological origin or historical development.
-
C.
etymologicalSource
Indicates that one term or name originates from, is derived from, or has its roots in another term or name.
-
D.
etymologicalNote
Indicates that there is a note explaining the origin, historical development, or source language of a term or name.
-
E.
etymologyGloss
chosen
Indicates that a term’s meaning is explained by a brief gloss specifically describing its etymological origin or source.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463cc493c8190965680cf786aa531 |
completed | April 19, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.