Triple
T38669967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Capital Region |
E940555
|
entity |
| Predicate | legislativeRegionNumber |
P89903
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [National Capital Region, legislativeRegionNumber, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legislativeRegionNumber Context triple: [National Capital Region, legislativeRegionNumber, 13]
-
A.
legislativeRegionCode
Indicates the specific legislative region or district code within which an entity falls or to which it is assigned.
-
B.
legislatureNumber
Indicates the specific numbered session or term of a legislative body associated with an entity or event.
-
C.
legislativeDistrictOf
Indicates that a specified geographic or political area is the legislative district in which a given entity (such as a person, organization, or location) is situated or represented.
-
D.
congressionalDistrictNumber
chosen
Indicates the specific numbered congressional district to which an entity (such as a location or representative) is assigned.
-
E.
legislativeRepresentationUnit
Indicates that one entity serves as a unit or body that provides legislative representation for another 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.