Triple
T7693719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magus |
E174313
|
entity |
| Predicate | workLanguageContext |
P8383
|
FINISHED |
| Object | Portuguese |
—
|
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: Portuguese | Statement: [Magus, workLanguageContext, Portuguese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLanguageContext Context triple: [Magus, workLanguageContext, Portuguese]
-
A.
languageOfInstitutionalContext
Indicates the language used as the primary medium of communication within an institutional setting or context.
-
B.
hasLanguageContext
chosen
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
C.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
D.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
E.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:02 p.m.