Triple
T9417886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Getty |
E227073
|
entity |
| Predicate | legalTrainingIn |
P25968
|
FINISHED |
| Object | law |
—
|
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: law | Statement: [George Getty, legalTrainingIn, law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalTrainingIn Context triple: [George Getty, legalTrainingIn, law]
-
A.
legalTraining
Indicates that one entity has provided or received education or instruction in law from another entity.
-
B.
legalSchoolPractice
Indicates that a particular legal practice, method, or approach is characteristic of, endorsed by, or derived from a specific school or tradition of law.
-
C.
legalPractice
Indicates a relationship where an entity engages in or is associated with the professional provision of legal services or the practice of law.
-
D.
legalBackground
chosen
Indicates that an entity has education, training, or experience related to law or the legal profession.
-
E.
legalRepresentation
Indicates that one entity formally acts on behalf of another in legal matters, such as providing counsel, advocacy, or defense within a legal system.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68cd1e3481909abcb715e2398120 |
completed | April 1, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:48 p.m.