Triple
T7900808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Provo Missionary Training Center |
E183446
|
entity |
| Predicate | hasLanguageTraining |
P54797
|
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: [Provo Missionary Training Center, hasLanguageTraining, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageTraining Context triple: [Provo Missionary Training Center, hasLanguageTraining, Spanish]
-
A.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
B.
hasLanguageModel
Indicates that an entity possesses, uses, or is associated with a particular language model.
-
C.
hasTrainingFor
chosen
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
D.
hasLinguist
Indicates that an entity is associated with or possesses a linguist, typically as a member, employee, collaborator, or resource.
-
E.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a3f4c2c81909ae70b0acf4729be |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:02 p.m.