Triple
T8221697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey state legislative districts |
E192077
|
entity |
| Predicate | seatsPerDistrictInSenate |
P38391
|
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: [New Jersey state legislative districts, seatsPerDistrictInSenate, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatsPerDistrictInSenate Context triple: [New Jersey state legislative districts, seatsPerDistrictInSenate, 1]
-
A.
numberOfSeatsInSenate
Indicates the total count of seats allocated in a given senate.
-
B.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
-
C.
minimumSeatsPerState
Indicates the smallest number of seats that must be allocated to each state in a representative body or legislative apportionment.
-
D.
eachDistrictElects
chosen
Indicates that every electoral district selects or chooses its own representative or set of representatives.
-
E.
maximumSeatsPerState
Indicates the upper limit on the number of seats that any single state is allowed to have.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb77c9680081909000fde3c9ae83ea |
completed | March 31, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69cb36af41e081909dee92b9bc4947f1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:45 p.m.