Triple
T2414541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Bedford for Great Britain |
E52271
|
entity |
| Predicate | conflictSideRepresented |
P375
|
FINISHED |
| Object | British side in the Seven Years’ War |
—
|
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: British side in the Seven Years’ War | Statement: [Duke of Bedford for Great Britain, conflictSideRepresented, British side in the Seven Years’ War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictSideRepresented Context triple: [Duke of Bedford for Great Britain, conflictSideRepresented, British side in the Seven Years’ War]
-
A.
conflictSide
chosen
Indicates that an entity participates as a distinct party or faction on one side of a conflict or dispute.
-
B.
conflictRole
Indicates that an entity plays a specific role or position within a conflict or dispute between parties.
-
C.
conflictStance
Indicates a party’s position, attitude, or alignment regarding a particular conflict or dispute.
-
D.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
E.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
- 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc94bd7ec81909f5b4a16a406165b |
completed | March 7, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_69abc5a6cbd0819086c0716e266b7ebb |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:41 p.m.