Triple
T13431682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oluta Popoluca |
E313625
|
entity |
| Predicate | hasDominantContactLanguage |
P46872
|
FINISHED |
| Object | Spanish |
—
|
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 | Statement: [Oluta Popoluca, hasDominantContactLanguage, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDominantContactLanguage Context triple: [Oluta Popoluca, hasDominantContactLanguage, Spanish]
-
A.
primaryLanguageContact
chosen
Indicates that one language serves as the main or dominant medium of communication in a particular contact situation between language communities.
-
B.
dominantMediaLanguage
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
-
C.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
D.
laterLanguageDominant
Indicates that one language becomes the dominant or primary language for an entity at a later point in time, after another language previously held that role.
-
E.
hasContactWithLanguage
Indicates that an entity has some form of interaction, exposure, or engagement with a particular language.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed41a5481908800033303224adb |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.