Triple
T5553092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Atzerodt |
E145573
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | George |
E22107
|
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: George | Statement: [George Atzerodt, givenName, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [George Atzerodt, givenName, George]
-
A.
George
chosen
George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
-
B.
George
George is the heroic protagonist of the fantasy film "The Magic Sword," known for embarking on a perilous quest to rescue a princess from an evil sorcerer.
-
C.
George
George is one of the central child detectives in Enid Blyton’s classic Secret Seven mystery series.
-
D.
George
George is the given name of George Washington Vanderbilt II, the American art collector and member of the prominent Vanderbilt family who built the Biltmore Estate.
-
E.
George
George is the birth name of the legendary American baseball player Babe Ruth, one of the sport’s most iconic figures.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ff9c9c48190b5e587d58c6515d8 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c059e7636c819082cc18b1913c08c9 |
completed | March 22, 2026, 9:06 p.m. |
Created at: March 22, 2026, 3:35 p.m.