Triple
T11889329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yurok language |
E282872
|
entity |
| Predicate | languageRevivalGoal |
P102084
|
FINISHED |
| Object | increase number of fluent speakers |
—
|
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: increase number of fluent speakers | Statement: [Yurok language, languageRevivalGoal, increase number of fluent speakers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageRevivalGoal Context triple: [Yurok language, languageRevivalGoal, increase number of fluent speakers]
-
A.
languageRevived
Indicates that a previously endangered or no-longer-spoken language has been brought back into active use within a community.
-
B.
languageRevivalMethod
Indicates the method or strategy used to revive or revitalize a language that is endangered, dormant, or no longer actively spoken.
-
C.
languageRevivalStart
Indicates the point in time when efforts to revive or revitalize a language begin.
-
D.
hasLanguageRevitalizationEfforts
Indicates that there are organized actions or initiatives aimed at preserving, strengthening, or reviving the use of a particular language.
-
E.
languageReform
Indicates efforts or actions aimed at changing, standardizing, or improving aspects of a language, such as its spelling, grammar, or usage rules.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a2860c8190a21af5fcddbd2f1e |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb2fca4481909893f3428b0871ac |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:44 p.m.