Triple
T714391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English law |
E14278
|
entity |
| Predicate | hasLegalProfession |
P5610
|
FINISHED |
| Object | barristers |
—
|
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: barristers | Statement: [English law, hasLegalProfession, barristers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalProfession Context triple: [English law, hasLegalProfession, barristers]
-
A.
legalProfessionRole
chosen
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
B.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
C.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
D.
hasLegalInstrument
Indicates that there exists a formal legal document or instrument that establishes, governs, or records the relationship between the related entities.
-
E.
regulatesProfession
Indicates that one entity has authority to control, oversee, or set rules governing the practice of a particular profession by 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5738e04819082eac673b3b7c4c2 |
completed | March 1, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f38898819089d79bad4f4ff2d2 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.