Triple
T4756468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schulich School of Law |
E105599
|
entity |
| Predicate | specializationArea |
P466
|
FINISHED |
| Object | marine and environmental 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: marine and environmental law | Statement: [Schulich School of Law, specializationArea, marine and environmental law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specializationArea Context triple: [Schulich School of Law, specializationArea, marine and environmental law]
-
A.
competenceArea
Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
-
B.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
C.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
D.
regionOfPractice
Indicates the geographic area or jurisdiction in which an entity regularly conducts its professional activities or services.
-
E.
regionOfAcademicFocus
Indicates the academic subject area or discipline that an entity (such as a person or program) primarily concentrates on or specializes in.
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64ec16a0819089836e4388b555f6 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd6223defc8190823665a6592c1154 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.