Triple
T14337070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Selection of Cases on the Law of Contracts |
E355491
|
entity |
| Predicate | inAcademicSubdiscipline |
P5461
|
FINISHED |
| Object | private 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: private law | Statement: [A Selection of Cases on the Law of Contracts, inAcademicSubdiscipline, private law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inAcademicSubdiscipline Context triple: [A Selection of Cases on the Law of Contracts, inAcademicSubdiscipline, private law]
-
A.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
B.
hasSubdiscipline
chosen
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
C.
housesAcademicDiscipline
Indicates that an entity serves as the location or institutional home where a particular academic discipline is based, organized, or conducted.
-
D.
regionOfAcademicFocus
Indicates the academic subject area or discipline that an entity (such as a person or program) primarily concentrates on or specializes in.
-
E.
regionOfAcademicInterest
Indicates that an entity has a particular academic field or subject area as its focus of interest or study.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c2241e48190a0c626b3d741966a |
completed | April 14, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69de2a9958e881909d03ac03f135163e |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:14 a.m.