Triple

T13113859
Position Surface form Disambiguated ID Type / Status
Subject Panketal E311041 entity
Predicate hasRailwayStation P918 FINISHED
Object Röntgental station
Röntgental station is a local railway stop serving the village of Röntgental in the municipality of Panketal, Brandenburg, Germany.
E1021837 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: Röntgental station | Statement: [Panketal, hasRailwayStation, Röntgental station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Röntgental station
Context triple: [Panketal, hasRailwayStation, Röntgental station]
  • A. Hengst station
    Hengst station is a mountain railway terminus serving as the upper endpoint of the Schneeberg line in Lower Austria.
  • B. Rommen station
    Rommen station is a metro stop in Oslo, Norway, located in the Groruddalen area and integrated into the city's rapid transit network.
  • C. Vestli station
    Vestli station is an Oslo Metro rapid transit station located in the Vestli neighborhood in the Stovner borough of Oslo, Norway.
  • D. Linderud station
    Linderud station is an Oslo Metro stop in the Linderud neighborhood, providing urban rail access on the city's east side.
  • E. Märsta Station
    Märsta Station is a key suburban railway hub in the town of Märsta, serving as a northern terminus and important node in the Stockholm commuter rail network.
  • 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: Röntgental station
Triple: [Panketal, hasRailwayStation, Röntgental station]
Generated description
Röntgental station is a local railway stop serving the village of Röntgental in the municipality of Panketal, Brandenburg, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Röntgental station
Target entity description: Röntgental station is a local railway stop serving the village of Röntgental in the municipality of Panketal, Brandenburg, Germany.
  • A. Hengst station
    Hengst station is a mountain railway terminus serving as the upper endpoint of the Schneeberg line in Lower Austria.
  • B. Rommen station
    Rommen station is a metro stop in Oslo, Norway, located in the Groruddalen area and integrated into the city's rapid transit network.
  • C. Vestli station
    Vestli station is an Oslo Metro rapid transit station located in the Vestli neighborhood in the Stovner borough of Oslo, Norway.
  • D. Linderud station
    Linderud station is an Oslo Metro stop in the Linderud neighborhood, providing urban rail access on the city's east side.
  • E. Märsta Station
    Märsta Station is a key suburban railway hub in the town of Märsta, serving as a northern terminus and important node in the Stockholm commuter rail network.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817f8ee8819084078b4bec5e4f18 completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27f5c4481909bc323c9d0c83dc9 completed May 3, 2026, 5:51 a.m.
NEDg Description generation batch_69f6e32bf5508190b4dc58971f8f64d0 completed May 3, 2026, 5:54 a.m.
NED2 Entity disambiguation (via description) batch_69f6e40a13c8819084daf9b77b46a181 completed May 3, 2026, 5:58 a.m.
Created at: April 9, 2026, 9:06 p.m.