Triple
T4129243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of the State of New Jersey |
E84999
|
entity |
| Predicate | senatorsPerDistrict |
P4272
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Government of the State of New Jersey, senatorsPerDistrict, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: senatorsPerDistrict Context triple: [Government of the State of New Jersey, senatorsPerDistrict, 1]
-
A.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
-
B.
numberOfSenators
chosen
Indicates the total count of senators associated with a given political body, region, or entity.
-
C.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
-
D.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
E.
numberOfSenates
Indicates the total count of senate bodies associated with or present in a given context or 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:42 p.m.