Triple

T2820852
Position Surface form Disambiguated ID Type / Status
Subject Langer See, Grünau E54804 entity
Predicate locatedIn P40 FINISHED
Object Grünau
Grünau is a waterside locality in Berlin known for its lakeside recreation areas, rowing facilities, and green residential surroundings.
 E313185 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: Grünau | Statement: [Langer See, Grünau, locatedIn, Grünau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Grünau
Context triple: [Langer See, Grünau, locatedIn, Grünau]
  • A. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • B. Schwandorf
    Schwandorf is a town in the Upper Palatinate region of Bavaria, Germany, known as a local administrative and commercial center on the Naab River.
  • C. Schaafheim
    Schaafheim is a municipality in the state of Hesse in central Germany.
  • D. Gunzenhausen
    Gunzenhausen is a historic town in Bavaria, Germany, known for its location on the Altmühl River and as a gateway to the Franconian Lake District.
  • E. Feuchtwangen
    Feuchtwangen is a historic town in Bavaria, Germany, known for its medieval architecture and location along the Romantic Road.
  • 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: Grünau
Triple: [Langer See, Grünau, locatedIn, Grünau]
Generated description
Grünau is a waterside locality in Berlin known for its lakeside recreation areas, rowing facilities, and green residential surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Grünau
Target entity description: Grünau is a waterside locality in Berlin known for its lakeside recreation areas, rowing facilities, and green residential surroundings.
  • A. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • B. Schwandorf
    Schwandorf is a town in the Upper Palatinate region of Bavaria, Germany, known as a local administrative and commercial center on the Naab River.
  • C. Schaafheim
    Schaafheim is a municipality in the state of Hesse in central Germany.
  • D. Gunzenhausen
    Gunzenhausen is a historic town in Bavaria, Germany, known for its location on the Altmühl River and as a gateway to the Franconian Lake District.
  • E. Feuchtwangen
    Feuchtwangen is a historic town in Bavaria, Germany, known for its medieval architecture and location along the Romantic Road.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde6e85008190a08eb2bf8e393e7e completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc4b8f688190827dfedda7a55828 completed March 11, 2026, 5:23 a.m.
NEDg Description generation batch_69b0fd4ec8c48190ad6cfd2b2b2c5425 completed March 11, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_69b0fda9e3e08190a765ebd814de8466 completed March 11, 2026, 5:29 a.m.
Created at: March 6, 2026, 9:59 p.m.