Triple
T1025714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Poland (Congress Poland) |
E22134
|
entity |
| Predicate | legalUnionType |
P10690
|
FINISHED |
| Object | personal union with the Russian crown |
—
|
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: personal union with the Russian crown | Statement: [Kingdom of Poland (Congress Poland), legalUnionType, personal union with the Russian crown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalUnionType Context triple: [Kingdom of Poland (Congress Poland), legalUnionType, personal union with the Russian crown]
-
A.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
B.
maritalBasis
Indicates that the relationship or status in question is founded on, justified by, or determined due to a marital relationship between the involved entities.
-
C.
allianceType
Indicates the specific kind or category of alliance relationship that exists between entities.
-
D.
inUnionFlagRepresents
Indicates that one entity is represented or symbolized by its inclusion on the union flag of another entity.
-
E.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7f4c66c8190b6098fb72c1465a3 |
completed | March 1, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69a4b72619cc8190932fdfa0c74dc055 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.