Triple
T28938783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Courts (Sondergerichte) |
E730388
|
entity |
| Predicate | punished |
P2287
|
FINISHED |
| Object | political opponents |
—
|
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: political opponents | Statement: [Special Courts (Sondergerichte), punished, political opponents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: punished Context triple: [Special Courts (Sondergerichte), punished, political opponents]
-
A.
punishedAmong
Indicates that an entity is punished within a particular group or set of entities, as one among them.
-
B.
punish
Indicates imposing a penalty or negative consequence on an entity in response to its perceived wrongdoing or rule violation.
-
C.
punishedBy
chosen
Indicates that an entity receives punishment administered by another entity.
-
D.
punishmentIncludes
Indicates that a specified punishment encompasses or contains another specified punitive measure as one of its components.
-
E.
punishedInAfterlife
Indicates that an entity is subjected to punishment or negative consequences in an afterlife or post-mortem realm.
- 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_69f043ea0aa88190a25acbf46157995a |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65b81d53881908f4e8f36867d2435 |
completed | May 2, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:34 a.m.