Triple
T3085360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guaymí |
E64357
|
entity |
| Predicate | endonymScript |
P16462
|
FINISHED |
| Object | Latin script |
—
|
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: Latin script | Statement: [Guaymí, endonymScript, Latin script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endonymScript Context triple: [Guaymí, endonymScript, Latin script]
-
A.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
B.
associatedLanguageScript
chosen
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
C.
hasLanguageOfToponym
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
D.
ethnonym
Indicates that one entity is the name of an ethnic group used to refer to the people associated with another entity.
-
E.
hasExonym
Indicates that one entity is known by an alternative name or designation in another language or cultural context.
- 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_69ad857bb4c88190a4cf27893fcabed8 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1eac5548190bee60ea8262c65a8 |
completed | March 8, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69ad9debb6308190be28378ae1fc98af |
completed | March 8, 2026, 4:03 p.m. |
Created at: March 8, 2026, 3:03 p.m.