Triple
T26864835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rotes Kloster |
E676435
|
entity |
| Predicate | hatSehenswürdigkeit |
P68764
|
FINISHED |
| Object | Klosterkirche des Heiligen Antonius der Einsiedler |
—
|
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: Klosterkirche des Heiligen Antonius der Einsiedler | Statement: [Rotes Kloster, hatSehenswürdigkeit, Klosterkirche des Heiligen Antonius der Einsiedler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hatSehenswürdigkeit Context triple: [Rotes Kloster, hatSehenswürdigkeit, Klosterkirche des Heiligen Antonius der Einsiedler]
-
A.
hasTouristAttractionRole
chosen
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
B.
heritageAttraction
Indicates that something is recognized or designated as a heritage-related attraction, typically of cultural, historical, or natural significance.
-
C.
typicalSights
Indicates that certain sights or visual features are commonly or characteristically observed in association with a given entity or context.
-
D.
notablePlace
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
-
E.
sights
Indicates that one entity perceives or observes another entity or object using vision.
- 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_69eee9ba94bc8190b44c5d4397d04ecd |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61e96d45881909f2b93dfc522064f |
completed | May 2, 2026, 3:56 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:28 a.m.