Triple
T11646801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prater Tower |
E276795
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | 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: Prater | Statement: [Prater Tower, location, Prater]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prater Context triple: [Prater Tower, location, Prater]
-
A.
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.
-
B.
Praza de Praterías
Praza de Praterías is a historic square in Santiago de Compostela’s old town, known for its Baroque architecture and its location beside the cathedral.
-
C.
Praterinsel
Praterinsel is a small island in the Isar River in central Munich, known for its cultural events, historic buildings, and riverside recreation.
-
D.
Vienna Prater
Vienna Prater is a historic amusement park and large public leisure area in Vienna, Austria, best known for its iconic Giant Ferris Wheel and traditional fairground attractions.
-
E.
Duden Park
Duden Park is a public green space in the Brussels municipality of Uccle, known for its wooded areas, walking paths, and recreational facilities.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2cc8bfc8190a063cc37de9596a9 |
completed | April 10, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4171833948190adafe71ab0d9d2de |
completed | May 1, 2026, 2:59 a.m. |
Created at: April 8, 2026, 9:39 p.m.