Triple
T14093727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austro-Russian-Saxon coalition |
E339197
|
entity |
| Predicate | typeOfConflictSide |
P1397
|
FINISHED |
| Object | anti-French coalition |
—
|
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: anti-French coalition | Statement: [Austro-Russian-Saxon coalition, typeOfConflictSide, anti-French coalition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfConflictSide Context triple: [Austro-Russian-Saxon coalition, typeOfConflictSide, anti-French coalition]
-
A.
conflictType
chosen
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
B.
conflictSide
Indicates that an entity participates as a distinct party or faction on one side of a conflict or dispute.
-
C.
conflictSideContext
Indicates that an entity participates in a conflict on a particular side, within a specified contextual framing (such as time, place, or specific phase of the conflict).
-
D.
conflictRole
Indicates that an entity plays a specific role or position within a conflict or dispute between parties.
-
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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ee47f0881908aea8b5231b93f2f |
completed | April 14, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.