Triple
T2432701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odelsting |
E52881
|
entity |
| Predicate | typeOfLegislationHandled |
P2588
|
FINISHED |
| Object | ordinary bills |
—
|
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: ordinary bills | Statement: [Odelsting, typeOfLegislationHandled, ordinary bills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLegislationHandled Context triple: [Odelsting, typeOfLegislationHandled, ordinary bills]
-
A.
typeOfLegislation
chosen
Indicates the specific category or kind of legislation that a given legal act or measure belongs to.
-
B.
areaOfLegislation
Indicates that one entity defines, concerns, or governs the legal domain or subject matter covered by another entity.
-
C.
hasLegislativeSubject
Indicates that a legislative document, action, or body concerns, addresses, or is about a particular subject or topic.
-
D.
hasLegislatureType
Indicates the specific form or system of legislature that an entity possesses or operates under.
-
E.
relatedLegislation
Indicates that there exists a legislative document that is connected to, affects, or is otherwise relevant to the subject entity.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcc74a5108190a3a9631b0cc1a127 |
completed | March 7, 2026, 6:57 a.m. |
| PD | Predicate disambiguation | batch_69abc5aa1b60819081b87f7985c6cff3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:43 p.m.