Triple
T2510853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rough Collie |
E52694
|
entity |
| Predicate | trainability |
P8715
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Rough Collie, trainability, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainability Context triple: [Rough Collie, trainability, high]
-
A.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
-
B.
trainingCharacteristic
Indicates that an entity has a specific property, feature, or quality related to training (such as method, intensity, or style).
-
C.
ability
chosen
Indicates that an entity has the capacity or power to perform a particular action or achieve a specific outcome.
-
D.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
E.
typicalTraining
Indicates that an entity commonly undergoes or is associated with a standard or usual form of training in relation to another entity or 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0bf37c0819088d28b5081ba7556 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.