Triple
T26984246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frau Frieda |
E679688
|
entity |
| Predicate | mainlyAppearsIn |
P795
|
FINISHED |
| Object | Kitchener-Waterloo Oktoberfest events |
—
|
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: Kitchener-Waterloo Oktoberfest events | Statement: [Frau Frieda, mainlyAppearsIn, Kitchener-Waterloo Oktoberfest events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainlyAppearsIn Context triple: [Frau Frieda, mainlyAppearsIn, Kitchener-Waterloo Oktoberfest events]
-
A.
appearsIn
chosen
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
B.
bestSeenIn
Indicates that something is most effectively or appropriately experienced, observed, or appreciated within a particular context, medium, or setting.
-
C.
appearsInSeries
Indicates that an entity is featured or occurs within a particular series.
-
D.
mayAppearOn
Indicates that one entity is allowed or able to be shown, featured, or present on another entity (such as a platform, medium, or surface).
-
E.
appearsInAdaptationBy
Indicates that an entity is featured or present in an adaptation created by a specified adapter (e.g., author, director, or studio).
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 6:47 a.m.