Triple
T9540877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean d’Orléans, Count of Dunois |
E230152
|
entity |
| Predicate | roleInSiegeOfOrléans |
P28183
|
FINISHED |
| Object | principal French commander inside the besieged city |
—
|
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: principal French commander inside the besieged city | Statement: [Jean d’Orléans, Count of Dunois, roleInSiegeOfOrléans, principal French commander inside the besieged city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInSiegeOfOrléans Context triple: [Jean d’Orléans, Count of Dunois, roleInSiegeOfOrléans, principal French commander inside the besieged city]
-
A.
roleInWarsOfTheRoses
Indicates the specific part or function an entity played in the historical conflict known as the Wars of the Roses.
-
B.
roleInFronde
Indicates that an entity participated in or held a specific role within the historical conflict known as the Fronde.
-
C.
roleInGallicWars
Indicates the role or involvement an entity had in the events or campaigns of the Gallic Wars.
-
D.
notableBattleRole
chosen
Indicates the specific role or function an entity played in a notable or historically significant battle.
-
E.
opponentInBattleOfCherbourg
Indicates that two entities were opposing sides against each other in the Battle of Cherbourg.
- F. None of above.
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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e695948190ab107fff38c57de7 |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.