Triple
T7083584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucile |
E165016
|
entity |
| Predicate | derivedFromLatinWord |
P5801
|
FINISHED |
| Object | lux |
—
|
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: lux | Statement: [Lucile, derivedFromLatinWord, lux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: derivedFromLatinWord Context triple: [Lucile, derivedFromLatinWord, lux]
-
A.
correspondsToLatinWord
Indicates that one element is the equivalent or matching term of another element in Latin.
-
B.
etymologicalRootMeaning
Indicates that one term’s meaning originates from or is derived from the historical or original meaning of another term.
-
C.
etymologicalSource
chosen
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.
etymologyRelatesTo
Indicates a relationship where one term’s origin, history, or derivation is connected to another linguistic form, word, 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5102be08190bbde790bfa8fe9e2 |
completed | March 27, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:40 p.m.