Triple
T1023388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galician language |
E22086
|
entity |
| Predicate | usesDefiniteArticle |
P5228
|
FINISHED |
| Object | o |
—
|
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: o | Statement: [Galician language, usesDefiniteArticle, o]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDefiniteArticle Context triple: [Galician language, usesDefiniteArticle, o]
-
A.
usesDefiniteArticlePosition
Indicates that a definite article appears in a specific syntactic or positional slot relative to another element in the expression.
-
B.
hasDefiniteArticle
chosen
Indicates that the referenced entity or term is accompanied by a definite article (such as "the") in the given context.
-
C.
hasNoIndefiniteArticle
Indicates that the related entity is expressed without an indefinite article (such as “a” or “an”) in the given linguistic context.
-
D.
usesPostpositions
Indicates that one entity employs postpositions, placing relational or grammatical markers after the words they modify rather than before them.
-
E.
hasDefinitenessDistinction
Indicates that a language or system grammatically distinguishes between definite and indefinite (or otherwise specified) reference in its expressions.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7e0f8908190bfe0a4cd8b31dfed |
completed | March 1, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69a4b72619cc8190932fdfa0c74dc055 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.