Triple
T29205311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Praia do Forte Novo |
E740393
|
entity |
| Predicate | hasCommonVisitorLanguages |
P110606
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Praia do Forte Novo, hasCommonVisitorLanguages, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonVisitorLanguages Context triple: [Praia do Forte Novo, hasCommonVisitorLanguages, English]
-
A.
hasPrimaryLanguageOfVisitors
chosen
Indicates that an entity is associated with the main language typically spoken or used by its visitors.
-
B.
hasCommonTranslationLanguage
Indicates that two entities share at least one language into which both can be or have been translated.
-
C.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
D.
hasMemberLanguage
Indicates that one entity is a language that is a constituent or member of a larger language group, family, or collection represented by the other entity.
-
E.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_6a004c41f13c8190bc47daf6a5ca3949 |
completed | May 10, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_6a004bce3e3081909b35ae5b3bf2b35e |
completed | May 10, 2026, 9:11 a.m. |
Created at: April 28, 2026, 12:09 p.m.