Triple
T15962065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billy McBride |
E387085
|
entity |
| Predicate | hasLegalSpecialty |
P86774
|
FINISHED |
| Object | civil litigation |
—
|
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: civil litigation | Statement: [Billy McBride, hasLegalSpecialty, civil litigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalSpecialty Context triple: [Billy McBride, hasLegalSpecialty, civil litigation]
-
A.
legalProfessionIncludes
chosen
Indicates that a legal profession or role encompasses, involves, or includes another specified legal function, specialization, or activity.
-
B.
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.
-
C.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
D.
hasLanguageOfPractice
Indicates that an entity uses or operates in a particular language as its regular or primary medium of practice.
-
E.
hasJurisprudenceField
Indicates that an entity’s work, expertise, or classification pertains to a specific field or branch of jurisprudence (legal theory or 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:53 a.m.