Triple
T1269466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paipai people |
E15675
|
entity |
| Predicate | languageEndangermentCause |
P23674
|
FINISHED |
| Object | language shift to 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: language shift to Spanish | Statement: [Paipai people, languageEndangermentCause, language shift to Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageEndangermentCause Context triple: [Paipai people, languageEndangermentCause, language shift to Spanish]
-
A.
languageEndangermentStatus
Indicates the degree to which a language is at risk of falling out of use or becoming extinct.
-
B.
causeOfLanguageShift
chosen
Indicates a factor or event that leads to a change from one dominant language or linguistic pattern to another within a community or population.
-
C.
languageDiversity
Indicates the degree to which multiple distinct languages are present and used within a given context or population.
-
D.
extinctionReason
Indicates the cause or factor responsible for an entity’s extinction.
-
E.
languageContactWith
Indicates a relationship where two or more languages come into contact through their speakers, leading to interaction and potential mutual influence.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c03aaa8c8190bacb7de5a38329da |
completed | March 1, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69a4bede52a081909665d60acbe41d31 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.