Triple
T20289226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Davis |
E509972
|
entity |
| Predicate | legalEducationIn |
P9439
|
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: [Philip Davis, legalEducationIn, law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalEducationIn Context triple: [Philip Davis, legalEducationIn, law]
-
A.
legalEducationFocus
Indicates that a legal education program, course, or experience is primarily centered on a particular area, topic, or specialization within the field of law.
-
B.
legalTraining
chosen
Indicates that one entity has provided or received education or instruction in law from another entity.
-
C.
legalEducationRequiredForPractice
Indicates that a specific type or level of legal education is required as a prerequisite for engaging in legal practice.
-
D.
legalSchoolFor
Indicates that one entity is an educational institution recognized or designated as a law school for another entity (such as a person, jurisdiction, or program).
-
E.
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.
- 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e67694d50881909d59c1037295c1d0 |
completed | April 20, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:10 a.m.