Triple
T2832201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolley Madison |
E62264
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Madison |
E61346
|
NE 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: Madison | Statement: [Dolley Madison, familyName, Madison]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madison Context triple: [Dolley Madison, familyName, Madison]
-
A.
Madison
chosen
Madison is a common English surname and given name, historically associated with U.S. President James Madison and now widely used as a first name, especially for girls.
-
B.
Madison
Madison is a suburban city in northern Alabama known for its proximity to Huntsville and its strong schools and residential communities.
-
C.
Racine
Racine is a city in southeastern Wisconsin located on the shore of Lake Michigan, known historically for its manufacturing industry and Danish kringle pastries.
-
D.
Milwaukie
Milwaukie is a small city in northwestern Oregon, located just south of Portland along the Willamette River.
-
E.
Monroe
Monroe is a mid-sized city in northeastern Louisiana known as a regional hub for commerce, education, and culture along the Ouachita River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebe95188190bf65fb4cd88e2ec5 |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afceb856d8819082d79b08433fe6d8 |
completed | March 10, 2026, 7:56 a.m. |
Created at: March 6, 2026, 10:01 p.m.