Triple
T12929699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leland McKenzie |
E309341
|
entity |
| Predicate | lawSpecialty |
P6403
|
FINISHED |
| Object | corporate law (implied) |
—
|
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 (implied) | Statement: [Leland McKenzie, lawSpecialty, corporate law (implied)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawSpecialty Context triple: [Leland McKenzie, lawSpecialty, corporate law (implied)]
-
A.
legalSystemSpecialization
Indicates that a legal system is specialized or tailored to address a particular domain, issue, or type of case within the broader legal framework.
-
B.
branchOfLaw
chosen
Indicates a relationship where one legal field or discipline is a subdivision or specialized area within a broader body of law.
-
C.
legalPractice
Indicates a relationship where an entity engages in or is associated with the professional provision of legal services or the practice of law.
-
D.
lawLibrary
Indicates a relationship where a location or resource functions as a library specifically dedicated to legal materials, services, or research.
-
E.
lawJournal
Indicates a relationship where a work is published in, associated with, or appears within a specific law journal.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.