Triple
T19779132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tampere Theatre |
E475084
|
entity |
| Predicate | usesStageTechnology |
P101251
|
FINISHED |
| Object | lighting design |
—
|
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: lighting design | Statement: [Tampere Theatre, usesStageTechnology, lighting design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesStageTechnology Context triple: [Tampere Theatre, usesStageTechnology, lighting design]
-
A.
usesStage
Indicates that one entity employs or operates on another entity at a particular phase or stage within a process or workflow.
-
B.
usesStageType
Indicates that one entity employs or operates with a particular type or category of stage.
-
C.
usedStage
Indicates that an entity made use of a particular stage or phase within a process, workflow, or lifecycle.
-
D.
stageTechnology
chosen
Indicates that a particular technology is used, implemented, or deployed at a specific stage or phase within a process, workflow, or lifecycle.
-
E.
enablesTechnology
Indicates that one entity makes it possible for another entity, system, or process to function through the use or provision of a particular technology.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6538230488190b45cd8aaec658f7f |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:49 p.m.