Triple
T4642829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kentucky Senate |
E101693
|
entity |
| Predicate | createsLawType |
P57553
|
FINISHED |
| Object | state 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: state statutes | Statement: [Kentucky Senate, createsLawType, state statutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: createsLawType Context triple: [Kentucky Senate, createsLawType, state statutes]
-
A.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
B.
legalCodeType
Indicates the specific category or classification of a legal code that applies to an entity or situation.
-
C.
legalCase
Indicates a relationship where a formal legal dispute or proceeding exists between parties, typically adjudicated by a court or similar authority.
-
D.
legalStandardCreated
Indicates that one entity (such as a case, statute, or regulation) establishes or formulates a legal standard that is then applied or referenced by another entity.
-
E.
legalCitationType
Indicates the specific kind or category of legal citation that characterizes the relationship between the citing and cited legal sources.
- 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a93047c8190990c94fd5a57c867 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5234d24c819095c79890b70eff9a |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:14 p.m.