Triple
T754306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stadttheater Fürth |
E15518
|
entity |
| Predicate | hasAudienceCapacity |
P16993
|
FINISHED |
| Object | medium-sized regional theatre |
—
|
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: medium-sized regional theatre | Statement: [Stadttheater Fürth, hasAudienceCapacity, medium-sized regional theatre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAudienceCapacity Context triple: [Stadttheater Fürth, hasAudienceCapacity, medium-sized regional theatre]
-
A.
hasAudienceSize
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
-
B.
audienceCapacityType
chosen
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
-
C.
hasAudience
Indicates that an entity is intended to be received, viewed, or engaged with by a particular group of people.
-
D.
hasAudienceReception
Indicates the relationship between a work or event and how it is received, perceived, or evaluated by its audience.
-
E.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64ecadc8190a82e25444e7abba6 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a501c4cc81908de6d63e3d4f60d7 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.