Triple
T236436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silesia |
E4833
|
entity |
| Predicate | wasSubjectOf |
P2830
|
FINISHED |
| Object | Silesian uprisings |
—
|
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: Silesian uprisings | Statement: [Silesia, wasSubjectOf, Silesian uprisings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasSubjectOf Context triple: [Silesia, wasSubjectOf, Silesian uprisings]
-
A.
notableWorkSubject
Indicates that a work is notably associated with a particular subject, such as a person, topic, or entity, as its primary focus or theme.
-
B.
subjectOfWork
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
-
C.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
D.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
E.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25ccab7648190be6e4f5febc1e313 |
completed | Feb. 28, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69a25b5dc640819092669575731c393f |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.