Triple
T32502680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silesian Museum in Opava |
E830705
|
entity |
| Predicate | oneOfTheOldestMuseumsIn |
P174518
|
FINISHED |
| Object | Czech Republic |
—
|
NE NERFINISHED |
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: Czech Republic | Statement: [Silesian Museum in Opava, oneOfTheOldestMuseumsIn, Czech Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oneOfTheOldestMuseumsIn Context triple: [Silesian Museum in Opava, oneOfTheOldestMuseumsIn, Czech Republic]
-
A.
isOldestMuseumIn
Indicates that a museum is the most ancient or earliest established museum within a specified location or region.
-
B.
isOldestPublicArtMuseumIn
Indicates that the subject is the oldest public art museum located within the specified place or region.
-
C.
isLargestMultipurposeMuseumIn
Indicates that a museum is the largest multipurpose museum within a specified geographic area or location.
-
D.
isOneOfLargestArtMuseumsIn
Indicates that the subject is among the largest art museums located in the specified place or region.
-
E.
isLargestMuseumIn
Indicates that a museum is the largest (by a specified measure, such as area, collection size, or visitors) among all museums within a given geographic or organizational scope.
- F. None of above. chosen
Provenance (4 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_69f349219cb8819087e120f509629c1b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c447cc8481909ecc03f5b914fc89 |
completed | May 3, 2026, 3:43 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c1b666188190ac43c3011a7df048 |
completed | May 3, 2026, 3:32 a.m. |
Created at: May 1, 2026, 12:59 a.m.