Triple
T3085345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guaymí |
E64357
|
entity |
| Predicate | autonymLanguageCode |
P45784
|
FINISHED |
| Object | ISO 639-3: gym |
—
|
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: ISO 639-3: gym | Statement: [Guaymí, autonymLanguageCode, ISO 639-3: gym]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: autonymLanguageCode Context triple: [Guaymí, autonymLanguageCode, ISO 639-3: gym]
-
A.
ethnicLanguageStatus
Indicates the status or role of a language in relation to a particular ethnic group (e.g., primary, secondary, heritage, or minority language).
-
B.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
C.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
D.
isCulturalLanguageOf
Indicates that a language serves as a primary medium of cultural expression, identity, and heritage for a particular group, community, or region.
-
E.
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.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:03 p.m.