Triple
T7140814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tennessee Code Annotated |
E166433
|
entity |
| Predicate | typeOfLawCollection |
P75075
|
FINISHED |
| Object | codified statutes |
—
|
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: codified statutes | Statement: [Tennessee Code Annotated, typeOfLawCollection, codified statutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLawCollection Context triple: [Tennessee Code Annotated, typeOfLawCollection, codified statutes]
-
A.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
B.
branchOfLaw
Indicates a relationship where one legal field or discipline is a subdivision or specialized area within a broader body of law.
-
C.
typeOfLawReport
Indicates the specific category or classification of a law report (e.g., official, unofficial, regional, specialized) associated with a legal case or decision.
-
D.
lawLibrary
Indicates a relationship where a location or resource functions as a library specifically dedicated to legal materials, services, or research.
-
E.
legalCodeFocus
Indicates that something is specifically concerned with, centered on, or primarily addressing a particular legal code or body of law.
- F. None of above. chosen
Provenance (4 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_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7775e408190b880abde0a3f8d12 |
completed | March 27, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c932888190b125ca3785b18553 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:45 p.m.