Triple
T23281655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert McClory |
E588877
|
entity |
| Predicate | practiced law in |
P2755
|
FINISHED |
| Object | Lake County, Illinois |
—
|
NE NERFINISHED |
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: Lake County, Illinois | Statement: [Robert McClory, practiced law in, Lake County, Illinois]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: practiced law in Context triple: [Robert McClory, practiced law in, Lake County, Illinois]
-
A.
practicedLawIn
chosen
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
B.
practicedInField
Indicates that an entity has engaged in practical work, training, or professional activity within a specified field or domain.
-
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.
hasCourtPractice
Indicates that an entity engages in or is associated with a particular court-related legal practice or activity.
-
E.
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.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19643b8908190a2c29552b272dc61 |
completed | April 29, 2026, 5:25 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:57 p.m.