Triple
T6319585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilha do Nogueira |
E141702
|
entity |
| Predicate | hasToponymLanguage |
P24399
|
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: [Ilha do Nogueira, hasToponymLanguage, Portuguese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToponymLanguage Context triple: [Ilha do Nogueira, hasToponymLanguage, Portuguese]
-
A.
hasLanguageOfToponym
chosen
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
B.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
C.
hasToponymicForm
Indicates that one entity is a toponymic (place-name-based) form or variant derived from another entity.
-
D.
hasToponymicDerivatives
Indicates that a name or term serves as the source from which related place-based or toponymic names are derived.
-
E.
hasToponymicUse
Indicates that a term or name is used as a toponym, i.e., as a place name or geographic designation.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064c4ed7c8190bd066dc7cd3d1329 |
completed | March 22, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69c060e5efc48190861b8266e5b0cc0c |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:29 p.m.