Triple
T14110043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis Du Pont Duchambon |
E339610
|
entity |
| Predicate | roleDuringSiegeOfLouisbourg1745 |
P112849
|
FINISHED |
| Object | French commander of the garrison |
—
|
LITERAL 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: French commander of the garrison | Statement: [Louis Du Pont Duchambon, roleDuringSiegeOfLouisbourg1745, French commander of the garrison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleDuringSiegeOfLouisbourg1745 Context triple: [Louis Du Pont Duchambon, roleDuringSiegeOfLouisbourg1745, French commander of the garrison]
-
A.
roleAtBattleOfMorlaix
Indicates the specific role, position, or function an entity held during the Battle of Morlaix.
-
B.
roleAtBattleOfToulon
Indicates the specific role, position, or function an entity held during the Battle of Toulon.
-
C.
roleInBattleOfHubbardton
Indicates the specific role or involvement an entity had in the Battle of Hubbardton.
-
D.
opponentInBattleOfCherbourg
Indicates that two entities were opposing sides against each other in the Battle of Cherbourg.
-
E.
roleInAmericanRevolution
Indicates that an entity had a specific role, position, or involvement in events or activities related to the American Revolution.
- F. None of above. chosen
Provenance (4 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de600caf308190ab6d8451ed4e3797 |
completed | April 14, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:22 p.m.