Triple
T14048765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agta languages |
E338027
|
entity |
| Predicate | areThreatenedBy |
P106049
|
FINISHED |
| Object | language shift to dominant Philippine languages |
—
|
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 dominant Philippine languages | Statement: [Agta languages, areThreatenedBy, language shift to dominant Philippine languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areThreatenedBy Context triple: [Agta languages, areThreatenedBy, language shift to dominant Philippine languages]
-
A.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
B.
isThreatenedCategory
Indicates that an entity belongs to a category facing risk of harm, decline, or extinction.
-
C.
threatToHumans
Indicates that the subject poses or represents a potential danger, harm, or risk to humans.
-
D.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
-
E.
isEndangeredDueTo
chosen
Indicates that an entity is endangered as a result of the specific cause or factor represented by the related entity.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c88b5e48190b0f0149102c08992 |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.