Triple
T8816229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum De Cruquius |
E209783
|
entity |
| Predicate | occupiesBuildingFromCentury |
P71096
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [Museum De Cruquius, occupiesBuildingFromCentury, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupiesBuildingFromCentury Context triple: [Museum De Cruquius, occupiesBuildingFromCentury, 19th century]
-
A.
locatedInBuildingConstructedInCentury
chosen
Indicates that something is located in a building whose construction dates to a specified century.
-
B.
constructionCentury
Indicates the century during which something was constructed or built.
-
C.
estimatedConstructionEndCentury
Indicates the century in which the construction of something is estimated to have been completed.
-
D.
acquiredInCentury
Indicates that one entity was acquired during a specific century represented by the other entity.
-
E.
existedInCentury
Indicates that an entity existed or was present during a specified century.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc600bd8a88190ad891a96201d796b |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c21e64c81908490e3b0875dc0d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:45 p.m.