Triple
T14183167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theatertreffen |
E351506
|
entity |
| Predicate | numberOfProductionsSelectedPerYear |
P57387
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Theatertreffen, numberOfProductionsSelectedPerYear, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfProductionsSelectedPerYear Context triple: [Theatertreffen, numberOfProductionsSelectedPerYear, 10]
-
A.
annualProductions
chosen
Indicates a relationship where a specified number or set of items is produced each year by an entity.
-
B.
totalProduction
Indicates the overall quantity of goods, services, or output produced by an entity or system over a specified period or within a defined scope.
-
C.
productionYears
Indicates the span of calendar years during which something was produced or manufactured.
-
D.
isFrequentlyProducedBy
Indicates that something is commonly or regularly generated, created, or brought about by a particular entity or source.
-
E.
notableProductionYear
Indicates the year in which an entity produced something considered notable or significant.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61cc0a848190b660095972b1223b |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:03 a.m.