Triple
T31951414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Araucanian |
E815787
|
entity |
| Predicate | hasLanguageExonym |
P4705
|
FINISHED |
| Object | Mapuche language |
—
|
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: Mapuche language | Statement: [Araucanian, hasLanguageExonym, Mapuche language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageExonym Context triple: [Araucanian, hasLanguageExonym, Mapuche language]
-
A.
hasExonym
chosen
Indicates that one entity is known by an alternative name or designation in another language or cultural context.
-
B.
hasExonymLanguageFamily
Indicates that an exonym is associated with a language family in which that exonym is used or from which it originates.
-
C.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
D.
hasEndonymLanguage
Indicates that the language specified is the one in which a name or term is expressed in its own native or local form.
-
E.
hasDemonymLanguage
Indicates that a language is used as the demonym (people’s name or adjective of nationality) for inhabitants of a particular place or group.
- 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_69f348f42d188190a33fc8d20ec50517 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe831c97c88190b27ecf100e25c2a0 |
completed | May 9, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69fe7f1b92648190b14e56bcaee5d0ca |
completed | May 9, 2026, 12:26 a.m. |
Created at: May 1, 2026, 12:07 a.m.