Triple
T20556049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ludwigsvorstadt-Isarvorstadt |
E504722
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Stachus area |
—
|
NE NERFINISHED |
How this triple was built (3 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: Stachus area | Statement: [Ludwigsvorstadt-Isarvorstadt, contains, Stachus area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stachus area Context triple: [Ludwigsvorstadt-Isarvorstadt, contains, Stachus area]
-
A.
Kleivstua area
The Kleivstua area is a scenic highland viewpoint and recreational spot in Hole, Norway, known for its panoramic views over the surrounding forests, lakes, and hills.
-
B.
Nordstan area
The Nordstan area is a major commercial district in central Gothenburg, Sweden, best known for its large shopping center and proximity to key transport hubs.
-
C.
Drusberg area
The Drusberg area is a mountainous region in the Swiss Alps known for its rugged terrain and alpine landscapes.
-
D.
Ruaka area
Ruaka area is a rapidly growing suburban neighborhood on the outskirts of Nairobi, Kenya, known for its residential developments and proximity to major shopping and business hubs.
-
E.
Sankt Gertrud area
Sankt Gertrud area is a historic district in central Malmö, Sweden, known for its preserved medieval street layout, old buildings, and mixed residential and commercial character.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stachus area Target entity description: The Stachus area is a major central square and bustling commercial hub in Munich, known for its historic Karlstor gate, shopping centers, and heavy pedestrian and transit traffic.
-
A.
Kleivstua area
The Kleivstua area is a scenic highland viewpoint and recreational spot in Hole, Norway, known for its panoramic views over the surrounding forests, lakes, and hills.
-
B.
Nordstan area
The Nordstan area is a major commercial district in central Gothenburg, Sweden, best known for its large shopping center and proximity to key transport hubs.
-
C.
Drusberg area
The Drusberg area is a mountainous region in the Swiss Alps known for its rugged terrain and alpine landscapes.
-
D.
Ruaka area
Ruaka area is a rapidly growing suburban neighborhood on the outskirts of Nairobi, Kenya, known for its residential developments and proximity to major shopping and business hubs.
-
E.
Sankt Gertrud area
Sankt Gertrud area is a historic district in central Malmö, Sweden, known for its preserved medieval street layout, old buildings, and mixed residential and commercial character.
- F. None of above. chosen
Provenance (2 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5dd02588190abddfcb868259a38 |
completed | April 20, 2026, 10:17 p.m. |
Created at: April 16, 2026, 11:38 a.m.