Triple
T36757302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2024 United States federal elections |
E908085
|
entity |
| Predicate | numberOfSpecialSenateElections |
P117794
|
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: [2024 United States federal elections, numberOfSpecialSenateElections, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSpecialSenateElections Context triple: [2024 United States federal elections, numberOfSpecialSenateElections, 1]
-
A.
hasSpecialElectionIn
Indicates that a special election is held within a specified political or geographic jurisdiction.
-
B.
hasSpeciallyElectedMembersCount
chosen
Indicates the number of members in a body or group who are chosen through a special or non-standard election process.
-
C.
canHoldSpecialElections
Indicates that an entity has the authority or ability to conduct special elections outside the regular election schedule.
-
D.
numberOfElectionsHeld
Indicates the total count of elections that have been conducted for a given entity or context.
-
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_69f76e779bec8190be0e1f87a131e0f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:12 p.m.