Triple
T276967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2020 United States presidential election |
E5269
|
entity |
| Predicate | involvedEvent |
P1256
|
FINISHED |
| Object | attempts to overturn the election results |
—
|
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: attempts to overturn the election results | Statement: [2020 United States presidential election, involvedEvent, attempts to overturn the election results]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedEvent Context triple: [2020 United States presidential election, involvedEvent, attempts to overturn the election results]
-
A.
involves
chosen
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
B.
participatedInEvent
Indicates that an entity took part in or was actively involved in a specific event.
-
C.
typicalEvent
Indicates that the associated event is a common, characteristic, or prototypical occurrence for the given entity or situation.
-
D.
introducedEvent
Indicates that an entity is responsible for bringing an event into existence or initiating it for the first time.
-
E.
coversEvent
Indicates that one event includes, spans, or encompasses the time period or occurrence of another event.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25ded68c88190b1fc595ce329aeb9 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7480e881909399beccfc7ffb81 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.