Triple
T18697232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huave of San Dionisio del Mar |
E457151
|
entity |
| Predicate | neighborLanguage |
P16383
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Huave of San Dionisio del Mar, neighborLanguage, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neighborLanguage Context triple: [Huave of San Dionisio del Mar, neighborLanguage, Spanish]
-
A.
hasNeighboringLanguageCommunity
Indicates that one language community is geographically or socially adjacent to another, allowing for direct contact or interaction between them.
-
B.
neighboringPeoples
Indicates that two peoples or ethnic groups live in adjacent or nearby territories, sharing a common border or close geographic proximity.
-
C.
hasNeighboringLanguages
chosen
Indicates that two languages are geographically or regionally adjacent to each other in their areas of use.
-
D.
languageLocalCommunities
Indicates that a language is used, maintained, or holds significance within specific local communities or regions.
-
E.
neighboringLanguageFamilies
Indicates that two language families are geographically adjacent or border each other in their primary regions of use.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e8bc408190ab41b3c21003c249 |
completed | April 19, 2026, 11:19 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.