Triple
T11090705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giacomo Maria |
E262244
|
entity |
| Predicate | hasEtymologicalOriginOfComponent_Giacomo |
P453
|
FINISHED |
| Object | derived from Jacobus |
—
|
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: derived from Jacobus | Statement: [Giacomo Maria, hasEtymologicalOriginOfComponent_Giacomo, derived from Jacobus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEtymologicalOriginOfComponent_Giacomo Context triple: [Giacomo Maria, hasEtymologicalOriginOfComponent_Giacomo, derived from Jacobus]
-
A.
etymologyProposedBy
Indicates that a proposed origin or derivation of a word or term is attributed to a particular person or source.
-
B.
hasNameInEtruscan
Indicates that an entity is associated with a specific name as it appears in the Etruscan language.
-
C.
etymologyStatus
Indicates the status or reliability classification of an etymological explanation for a term or name.
-
D.
etymology
chosen
Indicates the historical origin and development of a word or term, including its source language and form.
-
E.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799ebae8c8190987b474adb7ede47 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d744185a5881909ba4cf151d1798ec |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.