Triple
T21688981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michele Bachmann |
E535307
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michele Bachmann |
—
|
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: Michele Bachmann | Statement: [Michele Bachmann, name, Michele Bachmann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michele Bachmann Context triple: [Michele Bachmann, name, Michele Bachmann]
-
A.
Michele Bachmann
chosen
Michele Bachmann is an American politician and former Republican congresswoman from Minnesota known for her strong conservative and Tea Party-aligned positions.
-
B.
Michel Bachmann
Michel Bachmann is a French local politician serving as the mayor of the commune of Chauconin-Neufmontiers in the Île-de-France region.
-
C.
Bachmann
Bachmann is a German-language surname most notably associated with Austrian poet and writer Ingeborg Bachmann.
-
D.
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.
-
E.
Paul Ryan
Paul Ryan is an American Republican politician who served as the 54th Speaker of the U.S. House of Representatives and was the 2012 Republican nominee for vice president.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96cd51d481908df67e4f69826b06 |
completed | April 27, 2026, 5:03 p.m. |
Created at: April 16, 2026, 6:44 p.m.