Triple
T8646466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Generalstaatskommissar in Bavaria |
E204988
|
entity |
| Predicate | isEmergencyMeasure |
P84108
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Generalstaatskommissar in Bavaria, isEmergencyMeasure, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isEmergencyMeasure Context triple: [Generalstaatskommissar in Bavaria, isEmergencyMeasure, yes]
-
A.
hasEmergencyUse
Indicates that an entity is authorized, designated, or configured for use specifically in emergency situations or conditions.
-
B.
emergencyUse
Indicates that something is being used in response to an urgent or critical situation, typically as a temporary or exceptional measure.
-
C.
hasEmergencyLevel
Indicates that an entity is associated with a specific degree or severity of emergency status.
-
D.
emergencyPolicy
Indicates that an entity has a policy or set of rules specifically governing actions and procedures to be followed during emergencies or crisis situations.
-
E.
reasonForSpecialMeasures
Indicates that one entity specifies the justification or cause for which special measures or exceptional actions are taken regarding another entity.
- F. None of above. chosen
Provenance (4 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc480eb7f88190a38d2150976cd47f |
completed | March 31, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc473e44988190a3b02498e5fff668 |
completed | March 31, 2026, 10:14 p.m. |
Created at: March 30, 2026, 6:28 p.m.