Triple
T25345255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roxa |
E635527
|
entity |
| Predicate | hasCommonLanguageOfCountry |
P106335
|
FINISHED |
| Object | Guinea-Bissau Creole |
—
|
NE NERFINISHED |
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: Guinea-Bissau Creole | Statement: [Roxa, hasCommonLanguageOfCountry, Guinea-Bissau Creole]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonLanguageOfCountry Context triple: [Roxa, hasCommonLanguageOfCountry, Guinea-Bissau Creole]
-
A.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
B.
hasCommonTranslationLanguage
Indicates that two entities share at least one language into which both can be or have been translated.
-
C.
hasLanguageInCountry
chosen
Indicates that a particular language is used or recognized within a specified country.
-
D.
isLinguaFrancaOf
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
-
E.
isSpokenLanguageOf
Indicates that a particular language is used as the spoken language by a specified person, group, or community.
- 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_69e75a9ac5d881909387ed766e20cd47 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 21, 2026, 1:34 p.m.