Triple
T12432130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stendhal |
E297055
|
entity |
| Predicate | influencedBy |
P9
|
FINISHED |
| Object | Napoleon |
E1341
|
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: Napoleon | Statement: [Stendhal, influencedBy, Napoleon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Napoleon Context triple: [Stendhal, influencedBy, Napoleon]
-
A.
Napoleon
"Napoleon" is a satirical 1950 Broadway musical with lyrics by E. Y. Harburg that humorously reimagines the life and legacy of Napoleon Bonaparte.
-
B.
Napoleon
Napoleon is an American rapper best known for being a member of Tupac Shakur’s group Outlawz during the 1990s West Coast hip-hop era.
-
C.
Napoleón
Napoleón is a masculine given name of Spanish origin, famously borne by figures such as French emperor Napoleon Bonaparte and various Latin American political leaders.
-
D.
Napoleon Bonaparte
chosen
Napoleon Bonaparte was a French military general who rose to become Emperor of the French, dominating European affairs in the early 19th century through his political and military leadership.
-
E.
Bonaparte
Bonaparte is the prominent Corsican-origin dynasty best known for producing Napoleon Bonaparte and ruling France and parts of Europe in the early 19th century.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d7f2fd08190ab959742dbd8f9c0 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ea44a808190af2c5a6633120814 |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.