Triple
T15407269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nasarawa State House of Assembly |
E368491
|
entity |
| Predicate | typeOfLawProduced |
P57553
|
FINISHED |
| Object | state laws |
—
|
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 laws | Statement: [Nasarawa State House of Assembly, typeOfLawProduced, state laws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLawProduced Context triple: [Nasarawa State House of Assembly, typeOfLawProduced, state laws]
-
A.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
B.
typeOfLawCollection
Indicates that a given collection is categorized as a specific type of law collection (e.g., by legal domain, jurisdiction, or purpose).
-
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.
branchOfLaw
Indicates a relationship where one legal field or discipline is a subdivision or specialized area within a broader body of law.
-
E.
createsLawType
chosen
Indicates that an entity (such as a legislative body or authority) brings a specific type or category of law into existence.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea36c6881909eaea48e9608897a |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:20 a.m.