Triple
T4812927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tad Lincoln |
E107113
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lincoln |
E149651
|
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: Lincoln | Statement: [Tad Lincoln, familyName, Lincoln]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lincoln Context triple: [Tad 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 masculine given name of English origin most famously associated with U.S. President Abraham Lincoln.
-
C.
Lincoln
Lincoln is a suburban town in eastern Massachusetts known for its conservation land, historic sites, and commuter access to Boston.
-
D.
Lincoln
Lincoln is a historic cathedral city in the East Midlands of England, renowned for its medieval architecture, including Lincoln Cathedral and Lincoln Castle.
-
E.
Lincoln
chosen
Lincoln is a common English surname most famously associated with U.S. President Abraham Lincoln and his family.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6c7f11ec8190b2c5d365d4cc4709 |
completed | March 20, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fa2f3e0819084ca792c1b08e3b9 |
completed | March 21, 2026, 10:14 a.m. |
Created at: March 20, 2026, 1:23 p.m.