Triple
T1280240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Ottawa |
E27307
|
entity |
| Predicate | lawSchoolLanguage |
P17978
|
FINISHED |
| Object | common law in English |
—
|
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: common law in English | Statement: [University of Ottawa, lawSchoolLanguage, common law in English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawSchoolLanguage Context triple: [University of Ottawa, lawSchoolLanguage, common law in English]
-
A.
lawReview
Indicates a relationship where an entity is associated with a law review, typically as its subject, source, or venue of publication within legal scholarship.
-
B.
lawSchoolName
Indicates the name of the law school with which an entity (such as a person or institution) is associated.
-
C.
lawJournal
Indicates a relationship where a work is published in, associated with, or appears within a specific law journal.
-
D.
majorSchoolOfLaw
chosen
Indicates that a particular school of law is a primary or dominant legal tradition or framework associated with an entity.
-
E.
legalTraining
Indicates that one entity has provided or received education or instruction in law from 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c094eb4881909a33061339f91190 |
completed | March 1, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69a4bee276d8819092f71c5a1140bb61 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.