Triple
T18449796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Leopoldowna |
E450748
|
entity |
| Predicate | arrested in |
P24149
|
FINISHED |
| Object | 1741 |
—
|
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: 1741 | Statement: [Anna Leopoldowna, arrested in, 1741]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrested in Context triple: [Anna Leopoldowna, arrested in, 1741]
-
A.
arrestedFor
Indicates that an authority has taken someone into custody because they are suspected or accused of committing a specified offense or wrongdoing.
-
B.
arrestedWith
Indicates that two or more individuals were arrested at the same time and in connection with the same incident or operation.
-
C.
arrestedAt
chosen
Indicates that an entity was apprehended or taken into custody at a specific location or during a specific event or time.
-
D.
arrestIs
Indicates that one entity performs the action of arresting or taking another entity into legal custody.
-
E.
arrests
Indicates that one entity, typically an authority figure, seizes and detains another entity under legal or official power.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5264748dc8190984501af3e4b2036 |
completed | April 19, 2026, 7 p.m. |
| PD | Predicate disambiguation | batch_69e469d05cf4819099baf1665a9cf18a |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.