Triple
T7542459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel S. Dickinson |
E178312
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object | Stevens |
E26256
|
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: Stevens | Statement: [Daniel S. Dickinson, middleName, Stevens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stevens Context triple: [Daniel S. Dickinson, middleName, Stevens]
-
A.
Stevens
chosen
Stevens is a common English-language surname borne by numerous notable individuals across fields such as sports, politics, arts, and academia.
-
B.
Brant
Brant is a family name most notably associated with Isabella Brant, the first wife and frequent muse of the Flemish Baroque painter Peter Paul Rubens.
-
C.
Hillegas
Hillegas is a surname most notably associated with Michael Hillegas, the first Treasurer of the United States.
-
D.
Rutledge
Rutledge is a small town in eastern Tennessee that serves as the county seat of Grainger County within the Knoxville metropolitan area.
-
E.
Rutledge
Rutledge is a surname of English and Scottish origin borne by various notable individuals in politics, law, and other fields.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8762b048190a0b262f9cb3fe1b0 |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84f1d1e148190be015c62ae1ea1e8 |
completed | March 28, 2026, 9:58 p.m. |
Created at: March 27, 2026, 3:48 p.m.