Triple
T32496035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 United States Senate elections |
E830525
|
entity |
| Predicate | numberOfRegularSeatsForElection |
P11588
|
FINISHED |
| Object | 33 |
—
|
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: 33 | Statement: [2018 United States Senate elections, numberOfRegularSeatsForElection, 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRegularSeatsForElection Context triple: [2018 United States Senate elections, numberOfRegularSeatsForElection, 33]
-
A.
numberOfSeatsContested
chosen
Indicates the total count of seats in an election or contest that are being competed for or are up for selection.
-
B.
numberOfSeatsWon
Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
-
C.
numberOfElectedMembers
Indicates the total count of individuals who have been formally chosen through an election to serve as members of a given body or group.
-
D.
parliamentarySeatsTotal
Indicates the total number of seats in a given parliament or parliamentary body.
-
E.
electoralRegionSeatCount
Indicates the number of seats allocated to a given electoral region within a representative body or legislature.
- 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_69f349219cb8819087e120f509629c1b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01c21d8bc481909dd9f5a6b89c0a92 |
completed | May 11, 2026, 11:48 a.m. |
| PD | Predicate disambiguation | batch_6a01bff5d1508190895e5bd2c04932b0 |
completed | May 11, 2026, 11:39 a.m. |
Created at: May 1, 2026, 12:59 a.m.