Triple

T11174675
Position Surface form Disambiguated ID Type / Status
Subject Lake Schwerin E264378 entity
Predicate hasIsland P970 FINISHED
Object Ziegelwerder
Ziegelwerder is an island located within Lake Schwerin in northern Germany.
E908607 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: Ziegelwerder | Statement: [Lake Schwerin, hasIsland, Ziegelwerder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ziegelwerder
Context triple: [Lake Schwerin, hasIsland, Ziegelwerder]
  • A. Schierstein
    Schierstein is a riverside district of Wiesbaden in the German state of Hesse, known for its harbor and waterfront along the Rhine.
  • B. Werthhoven
    Werthhoven is a village-level district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • C. Zurenborg
    Zurenborg is a historic and architecturally distinctive district in Antwerp, Belgium, renowned for its eclectic and Art Nouveau townhouses.
  • D. Havelterberg
    Havelterberg is a modest hill and natural area in the Dutch province of Drenthe, known for its scenic landscapes and prehistoric burial mounds.
  • E. Neidenburg
    Neidenburg is the former German name for the town of Nidzica in northern Poland, historically part of East Prussia.
  • 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: Ziegelwerder
Triple: [Lake Schwerin, hasIsland, Ziegelwerder]
Generated description
Ziegelwerder is an island located within Lake Schwerin in northern Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ziegelwerder
Target entity description: Ziegelwerder is an island located within Lake Schwerin in northern Germany.
  • A. Schierstein
    Schierstein is a riverside district of Wiesbaden in the German state of Hesse, known for its harbor and waterfront along the Rhine.
  • B. Werthhoven
    Werthhoven is a village-level district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • C. Zurenborg
    Zurenborg is a historic and architecturally distinctive district in Antwerp, Belgium, renowned for its eclectic and Art Nouveau townhouses.
  • D. Havelterberg
    Havelterberg is a modest hill and natural area in the Dutch province of Drenthe, known for its scenic landscapes and prehistoric burial mounds.
  • E. Neidenburg
    Neidenburg is the former German name for the town of Nidzica in northern Poland, historically part of East Prussia.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e897774c819088ebc7231cebfba6 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e463c03a948190b0f40f657180c9bf completed April 19, 2026, 5:10 a.m.
NEDg Description generation batch_69e46c38bb4c819086a2aa9d86296419 completed April 19, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69e46db75d9c8190a84db52d58b71b96 completed April 19, 2026, 5:52 a.m.
Created at: April 8, 2026, 9:29 p.m.