Triple
T22815587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aquitani people |
E565087
|
entity |
| Predicate | laterRomanizedInto |
P149845
|
FINISHED |
| Object | Gallo-Roman population of Aquitania |
—
|
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: Gallo-Roman population of Aquitania | Statement: [Aquitani people, laterRomanizedInto, Gallo-Roman population of Aquitania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterRomanizedInto Context triple: [Aquitani people, laterRomanizedInto, Gallo-Roman population of Aquitania]
-
A.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
-
B.
hangulNameRomanized
Indicates that an entity’s Korean Hangul name is represented in its romanized (Latin alphabet) form.
-
C.
romanizationFrom
Indicates that one entity is a romanized representation derived from the script or writing system of another entity.
-
D.
partlyRomanized
Indicates that an entity has been converted into the Roman (Latin) script only in part, with some portions remaining in another script or unchanged.
-
E.
romanizationVariantOf
Indicates that one written form is a different romanized representation of the same underlying word or expression as another.
- F. None of above. chosen
Provenance (4 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dcb872881909a031d8560635fce |
completed | April 29, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:33 p.m.