Triple
T19903745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raúl Labrador |
E478357
|
entity |
| Predicate | legal practice area |
P80389
|
FINISHED |
| Object | immigration 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: immigration law | Statement: [Raúl Labrador, legal practice area, immigration law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legal practice area Context triple: [Raúl Labrador, legal practice area, immigration law]
-
A.
legalPractice
chosen
Indicates a relationship where an entity engages in or is associated with the professional provision of legal services or the practice of law.
-
B.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
C.
legalBackground
Indicates that an entity has education, training, or experience related to law or the legal profession.
-
D.
legalSchoolPractice
Indicates that a particular legal practice, method, or approach is characteristic of, endorsed by, or derived from a specific school or tradition of law.
-
E.
branchOfLaw
Indicates a relationship where one legal field or discipline is a subdivision or specialized area within a broader body of law.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65944c55481909b54a8f9a9c087d6 |
completed | April 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.