Triple
T20152137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Madison Cawthorn |
E491457
|
entity |
| Predicate | hasMiddleName |
P143
|
FINISHED |
| Object | Madison |
—
|
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: Madison | Statement: [David Madison Cawthorn, hasMiddleName, Madison]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madison Context triple: [David Madison Cawthorn, hasMiddleName, 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 coastal town in south-central Connecticut known for its beaches, historic New England charm, and popular Hammonasset Beach State Park.
-
C.
Madison
Madison is the capital city of Wisconsin, known for its lakes, vibrant university community, and progressive culture.
-
D.
Madison
Madison is the codename for a later-generation Itanium processor variant developed by Intel for high-end server and enterprise computing.
-
E.
Madison
Madison is a small town that serves as one of the local communities within Madison County.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667dc34e081908e42e4c1bde26170 |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:33 p.m.