Triple
T12445005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramo |
E297375
|
entity |
| Predicate | associatedWithLanguageName |
P63334
|
FINISHED |
| Object | Spanish language |
—
|
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: Spanish language | Statement: [Ramo, associatedWithLanguageName, Spanish language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithLanguageName Context triple: [Ramo, associatedWithLanguageName, Spanish language]
-
A.
linkedToLanguage
Indicates that an entity has an association or connection with a specific language, such as being expressed in, related to, or dependent on that language.
-
B.
closelyAssociatedLanguage
Indicates that one language is closely connected to another, such as through frequent co-use, mutual influence, or strong cultural or regional association.
-
C.
associatedWithTranslator
Indicates a relationship where an entity is linked or connected to a translator, typically as the translator of its content or language.
-
D.
coexistsWithLanguage
Indicates that one entity exists or functions alongside a particular language at the same time, without excluding or replacing it.
-
E.
alternateLanguageName
chosen
Indicates that an entity has an additional name or label in a different language from its primary or default name.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.