Triple
T1925563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Pope Cook |
E40821
|
entity |
| Predicate | typeOfLawPracticed |
P6527
|
FINISHED |
| Object | American 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: American law | Statement: [Daniel Pope Cook, typeOfLawPracticed, American law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLawPracticed Context triple: [Daniel Pope Cook, typeOfLawPracticed, American law]
-
A.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
B.
typeOfLaw
chosen
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
C.
branchOfLaw
Indicates a relationship where one legal field or discipline is a subdivision or specialized area within a broader body of law.
-
D.
practiceType
Indicates the specific kind or category of practice associated with an entity or activity.
-
E.
legalSystemWorkedOn
Indicates that a legal system has been applied to, influenced, or modified by some agent or process.
- 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_69a8864711648190b07bed24ed76258e |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb260da088190ac53bfc9437e112b |
completed | March 7, 2026, 5:06 a.m. |
| PD | Predicate disambiguation | batch_69abafeec6f881909d47acb966683279 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.