Triple
T4638854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rogers & Wells |
E101600
|
entity |
| Predicate | hasPracticeArea |
P17432
|
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: [Rogers & Wells, hasPracticeArea, corporate law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPracticeArea Context triple: [Rogers & Wells, hasPracticeArea, corporate law]
-
A.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
B.
hasPracticeFields
chosen
Indicates that an entity possesses or is associated with one or more designated fields or areas used for practice activities.
-
C.
hasJurisprudenceField
Indicates that an entity’s work, expertise, or classification pertains to a specific field or branch of jurisprudence (legal theory or law).
-
D.
hasPracticeIssue
Indicates that an entity is associated with a specific problem, concern, or challenge arising in practical or real-world practice.
-
E.
practiceType
Indicates the specific kind or category of practice associated with an entity or activity.
- 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a8e0ee88190becab97d2ef1571a |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5234d24c819095c79890b70eff9a |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.