Triple
T2538640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prater |
E56329
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Wurstelprater |
E56329
|
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: Wurstelprater | Statement: [Prater, hasPart, Wurstelprater]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wurstelprater Context triple: [Prater, hasPart, Wurstelprater]
-
A.
Stölzl
Stölzl is a German surname most notably associated with Gunta Stölzl, a pioneering textile artist and master at the Bauhaus.
-
B.
Prater
chosen
Prater is a large public park and historic amusement area in Vienna, Austria, best known for its iconic Giant Ferris Wheel and extensive green spaces.
-
C.
Burgplatz
Burgplatz is a historic central square in Braunschweig, Germany, known for its medieval architecture and prominent landmarks such as Dankwarderode Castle and the Brunswick Lion.
-
D.
Puch bei Hallein
Puch bei Hallein is a municipality in the Austrian state of Salzburg, known for its proximity to the city of Salzburg and its scenic Alpine surroundings.
-
E.
Kronenburgerpark
Kronenburgerpark is a historic public park in the Dutch city of Nijmegen, known for its medieval city wall, tower, and scenic green spaces.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd298fc2481908b2925bf6a06532b |
completed | March 7, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5cfc54cc8190bb43b54f873ffa63 |
completed | March 9, 2026, 11:51 p.m. |
Created at: March 6, 2026, 9:47 p.m.