Triple
T38695678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Heavy Vehicle Regulator |
E949988
|
entity |
| Predicate | typeOfLawAdministered |
P6527
|
FINISHED |
| Object | national uniform 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: national uniform law | Statement: [National Heavy Vehicle Regulator, typeOfLawAdministered, national uniform law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLawAdministered Context triple: [National Heavy Vehicle Regulator, typeOfLawAdministered, national uniform law]
-
A.
typeOfLaw
chosen
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.
legalSystemOverseen
Indicates that one entity has authority to supervise, administer, or control the operation of a particular legal system.
-
D.
typeOfLawCollection
Indicates that a given collection is categorized as a specific type of law collection (e.g., by legal domain, jurisdiction, or purpose).
-
E.
juridicalCategory
Indicates the legal classification or status under which an entity or relationship is formally recognized in a juridical system.
- 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:33 p.m.