Triple
T20677237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Juliet |
E508189
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object | James Maness |
—
|
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: James Maness | Statement: [Mount Juliet, hasMayor, James Maness]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Maness Context triple: [Mount Juliet, hasMayor, James Maness]
-
A.
James Maness
chosen
James Maness is a local American politician who has served as the mayor of Mt. Juliet, Tennessee.
-
B.
Cole Maness
Cole Maness is an American cyclist and former professional bike racer known publicly as the husband of actress Erika Christensen.
-
C.
Bill Manning
Bill Manning is an American sports executive best known for serving as president of Major League Soccer clubs, including Toronto FC and previously Real Salt Lake.
-
D.
Kevin Maney
Kevin Maney is an American technology journalist and author known for writing about the impact of emerging technologies on business and society.
-
E.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6bea24f288190928f828e5f567257 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 11:44 a.m.