Triple
T4075588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirchweihgottesdienst |
E86756
|
entity |
| Predicate | hatBesonderheit |
P19394
|
FINISHED |
| Object | Bezug auf Kirchenpatron |
—
|
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: Bezug auf Kirchenpatron | Statement: [Kirchweihgottesdienst, hatBesonderheit, Bezug auf Kirchenpatron]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hatBesonderheit Context triple: [Kirchweihgottesdienst, hatBesonderheit, Bezug auf Kirchenpatron]
-
A.
specialAppearance
Indicates that an entity makes a notable or exceptional appearance distinct from its usual or regular presence.
-
B.
specialFeature
chosen
Indicates that an entity possesses a distinctive or noteworthy attribute, capability, or characteristic that sets it apart from others.
-
C.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
D.
notableFeat
Indicates that an entity is recognized for having achieved or performed a particularly significant or distinguished feat.
-
E.
specialValue
Indicates that an entity possesses a distinguished or exceptional value compared to typical or default values in the given context.
- 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_69aed93ebe448190a1f1686e28740ac9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc25e2e08190b3c048e1b8f85bbf |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.