Triple
T36457405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theater an der Rott |
E898190
|
entity |
| Predicate | hasPrimaryLanguageAudience |
P94660
|
FINISHED |
| Object | German-speaking audience |
—
|
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: German-speaking audience | Statement: [Theater an der Rott, hasPrimaryLanguageAudience, German-speaking audience]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLanguageAudience Context triple: [Theater an der Rott, hasPrimaryLanguageAudience, German-speaking audience]
-
A.
hasTargetAudienceLanguage
chosen
Indicates that something is intended for or directed toward an audience that speaks a particular language.
-
B.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
C.
hasPrimaryLanguageOfVisitors
Indicates that an entity is associated with the main language typically spoken or used by its visitors.
-
D.
hasPrimaryLanguageOfOperations
Indicates that an entity conducts its main activities or operations primarily using a specified language.
-
E.
hasTargetAudienceRegion
Indicates that something is intended for or directed toward an audience located in a specific geographic region.
- 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_69f76e57f08481908593bd0bc34581c8 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:10 p.m.