Triple
T20908955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis-Philippe Demers |
E514883
|
entity |
| Predicate | typeOfLegalProfession |
P137974
|
FINISHED |
| Object | barrister |
—
|
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: barrister | Statement: [Louis-Philippe Demers, typeOfLegalProfession, barrister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLegalProfession Context triple: [Louis-Philippe Demers, typeOfLegalProfession, barrister]
-
A.
legalProfessionType
chosen
Indicates the specific category or type of legal profession associated with an entity (such as lawyer, judge, or notary).
-
B.
typeOfJurist
Indicates that one entity is a specific kind or category of jurist in relation to another entity.
-
C.
legalProfessionIncludes
Indicates that a legal profession or role encompasses, involves, or includes another specified legal function, specialization, or activity.
-
D.
legalProfessionRole
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
E.
legalProfessionTypeRegulated
Indicates that the specified type of legal profession is subject to formal regulation or oversight by an authority.
- 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_69e0b4f8a1108190bce3d31331290ced |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e901ca50819080b123af7977efbd |
completed | April 21, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:48 p.m.