Triple
T22703736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joni Ernst |
E561389
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Joni Ernst |
—
|
NE NERFINISHED |
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: Joni Ernst | Statement: [Joni Ernst, name, Joni Ernst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joni Ernst Context triple: [Joni Ernst, name, Joni Ernst]
-
A.
Joni Ernst
chosen
Joni Ernst is a Republican U.S. Senator from Iowa and the first woman elected to Congress from that state.
-
B.
Mari Blanchard
Mari Blanchard was an American film and television actress of the 1950s and 1960s, known for her roles in Westerns and adventure films.
-
C.
Kim Reynolds
Kim Reynolds is an American Republican politician serving as the governor of Iowa and known for her conservative policies on taxes, education, and public health.
-
D.
Staci Gruber
Staci Gruber is an American neuroscientist and researcher known for her work on the effects of marijuana on the brain and behavior.
-
E.
Melanie Beattie
Melanie Beattie is an American author and self-help writer best known for her influential work on codependency and recovery, including the bestselling book "Codependent No More."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178cca1e48190bbe7910f13692803 |
completed | April 29, 2026, 3:19 a.m. |
Created at: April 17, 2026, 3:16 p.m.