Triple
T4849014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Jefferson Eppes |
E108364
|
entity |
| Predicate | notableRelative |
P367
|
FINISHED |
| Object | Thomas Jefferson |
E1804
|
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: Thomas Jefferson | Statement: [Mary Jefferson Eppes, notableRelative, Thomas Jefferson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Jefferson Context triple: [Mary Jefferson Eppes, notableRelative, Thomas Jefferson]
-
A.
Thomas Jefferson
chosen
Thomas Jefferson was the third president of the United States, principal author of the Declaration of Independence, and a leading figure of early American political and intellectual life.
-
B.
Jefferson
Jefferson is the middle name of William Jefferson "Bill" Clinton, the 42nd president of the United States.
-
C.
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.
-
D.
Jefferson
Jefferson is the fictional Mississippi town that serves as the central setting in many of William Faulkner’s Yoknapatawpha County stories and novels.
-
E.
Jefferson
Jefferson is a domestic cat known by the given name "Jefferson."
- 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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d1c5594819094fe021d7717032d |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be778cace48190ad28eaf21aec7146 |
completed | March 21, 2026, 10:48 a.m. |
Created at: March 20, 2026, 1:25 p.m.