Triple
T10950011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reeperbahn |
E258700
|
entity |
| Predicate | regulatesActivityType |
P51774
|
FINISHED |
| Object | prostitution in designated side streets |
—
|
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: prostitution in designated side streets | Statement: [Reeperbahn, regulatesActivityType, prostitution in designated side streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatesActivityType Context triple: [Reeperbahn, regulatesActivityType, prostitution in designated side streets]
-
A.
hasActivityType
Indicates the specific kind or category of activity associated with an entity or event.
-
B.
permittedActivity
Indicates that a particular action or behavior is allowed or authorized within a given context or under specified rules.
-
C.
hasActivityRegulation
chosen
Indicates that one entity exerts control over the level, timing, or manner of another entity’s activity.
-
D.
mayRestrictActivity
Indicates that one entity has the authority or ability to limit, constrain, or prohibit certain actions or behaviors of another entity.
-
E.
regulatoryType
Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ed2f1c819081ec58457f57889d |
completed | April 9, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.