Triple
T19646965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doberman Pinscher |
E471698
|
entity |
| Predicate | practiceAssociatedWith |
P2458
|
FINISHED |
| Object | ear cropping |
—
|
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: ear cropping | Statement: [Doberman Pinscher, practiceAssociatedWith, ear cropping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: practiceAssociatedWith Context triple: [Doberman Pinscher, practiceAssociatedWith, ear cropping]
-
A.
associatedWithPractice
chosen
Indicates a relationship in which an entity is connected or linked to a particular practice, activity, or customary way of doing something.
-
B.
officeFollowedInPracticeBy
Indicates that one office or position is typically succeeded or implemented in practice by another office or position, even if not formally designated as its successor.
-
C.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
D.
practiceType
Indicates the specific kind or category of practice associated with an entity or activity.
-
E.
organizationAssociatedWith
Indicates that there is a formal or recognized connection or affiliation between an organization and 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64125dd9481908a891c71c975a964 |
completed | April 20, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.