Triple
T26245340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Senate election in Ohio, 2022 |
E656428
|
entity |
| Predicate | battlegroundStatus |
P12283
|
FINISHED |
| Object | battleground state race |
—
|
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: battleground state race | Statement: [U.S. Senate election in Ohio, 2022, battlegroundStatus, battleground state race]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battlegroundStatus Context triple: [U.S. Senate election in Ohio, 2022, battlegroundStatus, battleground state race]
-
A.
battlefieldStatus
Indicates the current condition or situation of forces and events within a combat or conflict area.
-
B.
keyBattlegroundState
chosen
Indicates that a location is considered a crucial battleground state whose outcome is highly influential in determining the overall result of an election.
-
C.
battlegroundType
Indicates the specific kind or category of environment in which a battle or conflict takes place.
-
D.
statusDuringBattle
Indicates the condition or state an entity has while a specific battle or combat event is taking place.
-
E.
opposingForcesStatus
Indicates the current state or condition of two or more forces that are in conflict or opposition to each other.
- 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_69ee5b4c59a881909d9ee4fd013fffd5 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60dc5cbc48190952960eeab21cc9f |
completed | May 2, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69f60b874cc88190a487230abb69efea |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 9:05 p.m.