Triple
T12070953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint John of Nepomuk |
E287418
|
entity |
| Predicate | hasStatuesIn |
P1646
|
FINISHED |
| Object | Central Europe |
—
|
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: Central Europe | Statement: [Saint John of Nepomuk, hasStatuesIn, Central Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatuesIn Context triple: [Saint John of Nepomuk, hasStatuesIn, Central Europe]
-
A.
hasStatue
chosen
Indicates that one entity possesses, contains, or is associated with a statue representing or located within it.
-
B.
hasMuseumAt
Indicates that a museum is located at or exists in a specified place or location.
-
C.
hasStatueOrigin
Indicates that a statue was created in, derived from, or originally located in a specified place or source.
-
D.
hasCommemorativeStructure
Indicates that one entity possesses or is associated with a physical structure created to honor, remember, or commemorate another entity or event.
-
E.
hasNumberOfMonuments
Indicates the specific count of monuments associated with or present in a given entity.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.