Triple
T10441535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baden bei Wien |
E246180
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object |
Trinkhalle
Trinkhalle is a historic spa pavilion in Baden bei Wien, Austria, known for its elegant architecture and role in the town’s traditional bathing and health culture.
|
E863146
|
NE FINISHED |
How this triple was built (4 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: Trinkhalle | Statement: [Baden bei Wien, hasAttraction, Trinkhalle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trinkhalle Context triple: [Baden bei Wien, hasAttraction, Trinkhalle]
-
A.
Schoppen
Schoppen is a small village that forms part of the municipality of Amel in the German-speaking Community of eastern Belgium.
-
B.
Looshaus
Looshaus is a pioneering early modernist building in Vienna, Austria, designed by architect Adolf Loos and renowned for its radical rejection of ornament.
-
C.
Recepturhaus
Recepturhaus is a historic building and notable architectural landmark in the town of Kronberg im Taunus, Germany.
-
D.
Waidhaus
Waidhaus is a municipality in eastern Bavaria, Germany, near the Czech border, known as a key road border crossing and transport hub.
-
E.
Seelbach
Seelbach is a municipality in southwestern Germany’s Baden-Württemberg region, situated in the Ortenau district near the Black Forest.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Trinkhalle Triple: [Baden bei Wien, hasAttraction, Trinkhalle]
Generated description
Trinkhalle is a historic spa pavilion in Baden bei Wien, Austria, known for its elegant architecture and role in the town’s traditional bathing and health culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trinkhalle Target entity description: Trinkhalle is a historic spa pavilion in Baden bei Wien, Austria, known for its elegant architecture and role in the town’s traditional bathing and health culture.
-
A.
Schoppen
Schoppen is a small village that forms part of the municipality of Amel in the German-speaking Community of eastern Belgium.
-
B.
Looshaus
Looshaus is a pioneering early modernist building in Vienna, Austria, designed by architect Adolf Loos and renowned for its radical rejection of ornament.
-
C.
Recepturhaus
Recepturhaus is a historic building and notable architectural landmark in the town of Kronberg im Taunus, Germany.
-
D.
Waidhaus
Waidhaus is a municipality in eastern Bavaria, Germany, near the Czech border, known as a key road border crossing and transport hub.
-
E.
Seelbach
Seelbach is a municipality in southwestern Germany’s Baden-Württemberg region, situated in the Ortenau district near the Black Forest.
- F. None of above. chosen
Provenance (5 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fb9ebf488190ae776bd65e94cb00 |
completed | April 7, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ed6edd88190afd5063daba58a46 |
completed | April 10, 2026, 4:38 a.m. |
| NEDg | Description generation | batch_69d8837f98e08190bbffa535f94daf48 |
completed | April 10, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d889d0e70c8190953d164f34f01e47 |
completed | April 10, 2026, 5:25 a.m. |
Created at: April 6, 2026, 12:15 p.m.