Triple
T1839298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oktoberfest |
E41136
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Wiesn |
E118422
|
NE 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: Wiesn | Statement: [Oktoberfest, alsoKnownAs, Wiesn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wiesn Context triple: [Oktoberfest, alsoKnownAs, Wiesn]
-
A.
Oktoberfest
Oktoberfest is a world-famous annual beer and folk festival held in Munich, Germany, known for its large beer tents, traditional Bavarian music, food, and costumes.
-
B.
Theresienwiese
chosen
Theresienwiese is a large open space in Munich, Germany, best known as the traditional site of the annual Oktoberfest beer festival.
-
C.
Michaelis-Kirchweih
Michaelis-Kirchweih is a traditional Franconian folk and church fair, renowned as one of Bavaria’s oldest and largest street festivals, held annually in Fürth around Michaelmas.
-
D.
Bayreuth
Bayreuth is a city in northern Bavaria, Germany, best known for its association with composer Richard Wagner and its annual Bayreuth Festival of his operas.
-
E.
Bad Driburg
Bad Driburg is a small spa town in North Rhine-Westphalia, Germany, known for its mineral springs and health resorts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb03b3eb08190ae68d8476fc89c7f |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc9b93cd08190a467b56a0c0bd957 |
completed | March 8, 2026, 7:10 p.m. |
Created at: March 4, 2026, 7:33 p.m.