Triple
T1842105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waldeck |
E41198
|
entity |
| Predicate | foreignService |
P34036
|
FINISHED |
| Object | served in British Army as auxiliaries |
—
|
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: served in British Army as auxiliaries | Statement: [Waldeck, foreignService, served in British Army as auxiliaries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foreignService Context triple: [Waldeck, foreignService, served in British Army as auxiliaries]
-
A.
foreignPolicyContext
Indicates the broader international relations setting or circumstances within which a foreign policy decision, action, or stance occurs.
-
B.
foreignPolicyProgram
Indicates a program or initiative that defines, guides, or implements a state's foreign policy toward other international actors.
-
C.
foreignPolicyArea
Indicates the specific domain or topic within foreign policy to which an action, decision, or statement is related.
-
D.
foreignPolicyEvent
Indicates an event involving actions, decisions, or developments in a state’s relations with other countries or international actors.
-
E.
serviceOf
Indicates that one entity performs, provides, or fulfills a function or duty on behalf of another entity.
- 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdb0d2c8190a67f584e67979fa3 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb32a8d548190a231c7c2ce276a5e |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:33 p.m.