Triple
T19809071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Lincoln |
E475893
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lincoln |
—
|
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: Lincoln | Statement: [Thomas Lincoln, familyName, Lincoln]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lincoln Context triple: [Thomas Lincoln, familyName, Lincoln]
-
A.
Lincoln
Lincoln is a luxury automobile marque of the Ford Motor Company known for its premium sedans and SUVs.
-
B.
Lincoln
Lincoln is a historic cathedral city in the East Midlands of England, renowned for its medieval architecture, including Lincoln Cathedral and Lincoln Castle.
-
C.
Lincoln
Lincoln is a suburban town in Providence County, Rhode Island, known for its historic mill villages, residential neighborhoods, and recreational areas such as Lincoln Woods State Park.
-
D.
Lincoln
chosen
Lincoln is a masculine given name of English origin most famously associated with U.S. President Abraham Lincoln.
-
E.
Lincoln
Lincoln is a small city in Talladega County, Alabama, known for its proximity to the Talladega Superspeedway and Logan Martin Lake.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6542ac1b48190a0cb69dbceca74da |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:50 p.m.