Triple
T1456390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cieszyn Silesia |
E31409
|
entity |
| Predicate | wasDividedInYear |
P9346
|
FINISHED |
| Object | 1920 |
—
|
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: 1920 | Statement: [Cieszyn Silesia, wasDividedInYear, 1920]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasDividedInYear Context triple: [Cieszyn Silesia, wasDividedInYear, 1920]
-
A.
wasDividedFromYear
chosen
Indicates that an entity began to be separated or partitioned starting from a specified year.
-
B.
wasDividedByTreaty
Indicates that an entity (such as a territory or region) was partitioned or separated as the result of a formal treaty or agreement.
-
C.
historicallyDividedInto
Indicates that an entity was separated into multiple distinct parts or regions during a past historical period.
-
D.
diplomaticRelationsSeveredYear
Indicates the year in which formal diplomatic relations between the referenced parties were officially severed.
-
E.
separationYear
Indicates the year in which two entities ended or dissolved their relationship or association.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c598b30c8190b87207adf608b89a |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47cdbd0819092022344a2f4ad7b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.