Triple
T36689832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polish population transfers after World War II |
E905925
|
entity |
| Predicate | alsoAffected |
P142521
|
FINISHED |
| Object | Ukrainians |
—
|
NE NERFINISHED |
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: Ukrainians | Statement: [Polish population transfers after World War II, alsoAffected, Ukrainians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoAffected Context triple: [Polish population transfers after World War II, alsoAffected, Ukrainians]
-
A.
alsoAffects
chosen
Indicates that an action, condition, or change impacting one entity additionally impacts another entity as well.
-
B.
areAffectedBy
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
C.
standAffected
Indicates that an entity is in a state or position of being impacted or influenced by another entity or event.
-
D.
affectsRelationshipBetween
Indicates that one entity causes a change or influence on the nature, quality, or status of the relationship between two or more other entities.
-
E.
affectedSubject
Indicates that an entity is the one that experiences or is impacted by an action, event, or condition.
- 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_69f76e70d2448190bdd3ce781ba971c5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c7c6af7481908ecf292751c40569 |
completed | May 3, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.