Triple
T3532980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Basic School |
E74702
|
entity |
| Predicate | usesTrainingMethod |
P16019
|
FINISHED |
| Object | field exercises |
—
|
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: field exercises | Statement: [The Basic School, usesTrainingMethod, field exercises]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTrainingMethod Context triple: [The Basic School, usesTrainingMethod, field exercises]
-
A.
trainingMethod
chosen
Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
-
B.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
C.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
D.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
E.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc9b945481909867d44b810e8b1f |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae13ab808190a5d6ecdc7543445e |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.