Triple
T2318035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France and Austria |
E51109
|
entity |
| Predicate | relationshipCharacterizedBy |
P10690
|
FINISHED |
| Object | shifting alliances |
—
|
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: shifting alliances | Statement: [France and Austria, relationshipCharacterizedBy, shifting alliances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipCharacterizedBy Context triple: [France and Austria, relationshipCharacterizedBy, shifting alliances]
-
A.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
B.
relatedCharacter
Indicates that one character has a specified relationship or association with another character.
-
C.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
E.
fictionalRelationship
Indicates a relationship that exists only within a fictional or imagined context between 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.