Triple
T78080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perkins Coie |
E1562
|
entity |
| Predicate | practiceArea |
P2167
|
FINISHED |
| Object | corporate 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: corporate law | Statement: [Perkins Coie, practiceArea, corporate law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: practiceArea Context triple: [Perkins Coie, practiceArea, corporate law]
-
A.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
B.
legalArea
chosen
Indicates the specific field or branch of law that a legal matter, case, or document pertains to.
-
C.
legalSubject
Indicates that an entity is the bearer of legal rights, duties, or responsibilities within a legal relationship or context.
-
D.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
E.
constitutionalDomain
Indicates that something falls within the scope, authority, or subject matter defined or governed by a particular constitution.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.