Triple
T11883877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson Davis |
E282726
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jefferson |
E887246
|
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: Jefferson | Statement: [Jefferson Davis, givenName, Jefferson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jefferson Context triple: [Jefferson Davis, givenName, Jefferson]
-
A.
Jefferson
Jefferson is a small city in northeastern Georgia that serves as the county seat of Jackson County and lies within the state's historic gold-mining region.
-
B.
Jefferson
Jefferson is a domestic cat known by the given name "Jefferson."
-
C.
Jefferson
Jefferson is a city in Iowa, United States, known as the birthplace of pioneering American pollster George Gallup.
-
D.
Jefferson
Jefferson is the family name of Stan Laurel, the famed English comic actor and one half of the legendary film duo Laurel and Hardy.
-
E.
Jefferson
chosen
Jefferson is the given name of Jefferson C. Davis, a controversial American military officer who served as a Union general during the Civil War.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a02ad4819090faef0e0be732ee |
completed | April 10, 2026, 10:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f417da310c8190aa04df2a316a5dd0 |
completed | May 1, 2026, 3:02 a.m. |
Created at: April 8, 2026, 9:44 p.m.