Triple
T2538680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prater |
E56329
|
entity |
| Predicate | hasGermanName |
P1435
|
FINISHED |
| Object | Wiener Prater |
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: Wiener Prater | Statement: [Prater, hasGermanName, Wiener Prater]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wiener Prater Context triple: [Prater, hasGermanName, Wiener Prater]
-
A.
Bundesplatz
Bundesplatz is the central public square in Bern, Switzerland, located in front of the Federal Palace and often used for political events, markets, and public gatherings.
-
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.
Hofgarten
The Hofgarten is a historic Renaissance-style court garden in central Munich, known for its arcades, pavilions, and role as a popular public park and cultural venue.
-
D.
Kronenburgerpark
Kronenburgerpark is a historic public park in the Dutch city of Nijmegen, known for its medieval city wall, tower, and scenic green spaces.
-
E.
Leopoldplatz
Leopoldplatz is a major public square and important transport hub in Berlin’s Wedding district, served by multiple U-Bahn lines and numerous bus routes.
- 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_69af65573c30819080a8f0235e5dd8be |
completed | March 10, 2026, 12:27 a.m. |
Created at: March 6, 2026, 9:47 p.m.