Triple
T23345644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friesenberg tram stop |
E591855
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Friesenberg
Friesenberg is a residential district in the city of Zurich, Switzerland, situated on the lower slopes of the Uetliberg mountain.
|
E1583990
|
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: Friesenberg | Statement: [Friesenberg tram stop, locatedIn, Friesenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Friesenberg Context triple: [Friesenberg tram stop, locatedIn, Friesenberg]
-
A.
Friedeberg
Friedeberg is a historic town that served as one of the principal urban centers of the Neumark region in former Brandenburg, now located in western Poland.
-
B.
Odershausen
Odershausen is a village and district of the spa town Bad Wildungen in the state of Hesse, Germany.
-
C.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
D.
Frankenhausen
Frankenhausen is a town in central Germany historically notable as the site of the decisive 1525 Battle of Frankenhausen during the German Peasants' War.
-
E.
Friesdorf
Friesdorf is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
- 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: Friesenberg Triple: [Friesenberg tram stop, locatedIn, Friesenberg]
Generated description
Friesenberg is a residential district in the city of Zurich, Switzerland, situated on the lower slopes of the Uetliberg mountain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Friesenberg Target entity description: Friesenberg is a residential district in the city of Zurich, Switzerland, situated on the lower slopes of the Uetliberg mountain.
-
A.
Friedeberg
Friedeberg is a historic town that served as one of the principal urban centers of the Neumark region in former Brandenburg, now located in western Poland.
-
B.
Odershausen
Odershausen is a village and district of the spa town Bad Wildungen in the state of Hesse, Germany.
-
C.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
D.
Frankenhausen
Frankenhausen is a town in central Germany historically notable as the site of the decisive 1525 Battle of Frankenhausen during the German Peasants' War.
-
E.
Friesdorf
Friesdorf is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
- 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1983697408190b31817174ed4e77b |
completed | April 29, 2026, 5:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c5dca8a488190b9b128e366234663 |
completed | May 19, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_6a0c61b4476481909ad7cea089084141 |
completed | May 19, 2026, 1:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c620a75cc81908b6ded8fd02951e7 |
completed | May 19, 2026, 1:13 p.m. |
Created at: April 17, 2026, 5:19 p.m.