Triple

T20037789
Position Surface form Disambiguated ID Type / Status
Subject Schöneberg E497321 entity
Predicate hasLandmark P105 FINISHED
Object Winterfeldtplatz
Winterfeldtplatz is a well-known square in Berlin famous for its large weekly market and vibrant neighborhood atmosphere.
 E1406882 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: Winterfeldtplatz | Statement: [Schöneberg, hasLandmark, Winterfeldtplatz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Winterfeldtplatz
Context triple: [Schöneberg, hasLandmark, Winterfeldtplatz]
  • A. Schönfeldwiese
    Schönfeldwiese is a well-known open meadow in Munich’s Englischer Garten, popular for sunbathing, recreation, and its long tradition of nude bathing.
  • B. Hinterfeld
    Hinterfeld is a locality within the town of Langenfeld in the Rhineland region of western Germany.
  • C. Stadtlengsfeld
    Stadtlengsfeld is a small town in the Wartburg district of Thuringia, Germany, known historically as a rural community in central Germany.
  • D. Buttenwiesen
    Buttenwiesen is a municipality in the Bavarian region of Swabia in southern Germany, known for its rural character and location along the Danube River.
  • E. Falkeplatz
    Falkeplatz is a location in Chemnitz, Germany, known for hosting cultural institutions such as the Museum Gunzenhauser.
  • 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: Winterfeldtplatz
Triple: [Schöneberg, hasLandmark, Winterfeldtplatz]
Generated description
Winterfeldtplatz is a well-known square in Berlin famous for its large weekly market and vibrant neighborhood atmosphere.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Winterfeldtplatz
Target entity description: Winterfeldtplatz is a well-known square in Berlin famous for its large weekly market and vibrant neighborhood atmosphere.
  • A. Schönfeldwiese
    Schönfeldwiese is a well-known open meadow in Munich’s Englischer Garten, popular for sunbathing, recreation, and its long tradition of nude bathing.
  • B. Hinterfeld
    Hinterfeld is a locality within the town of Langenfeld in the Rhineland region of western Germany.
  • C. Stadtlengsfeld
    Stadtlengsfeld is a small town in the Wartburg district of Thuringia, Germany, known historically as a rural community in central Germany.
  • D. Buttenwiesen
    Buttenwiesen is a municipality in the Bavarian region of Swabia in southern Germany, known for its rural character and location along the Danube River.
  • E. Falkeplatz
    Falkeplatz is a location in Chemnitz, Germany, known for hosting cultural institutions such as the Museum Gunzenhauser.
  • 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_69da627278c88190babe4297a9df1236 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662e935ac8190900cdb4f0cfde505 completed April 20, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a080e39542c8190b94ae9d8212026a8 completed May 16, 2026, 6:27 a.m.
NEDg Description generation batch_6a080ec9c56481908b69834b5a1ae105 completed May 16, 2026, 6:29 a.m.
NED2 Entity disambiguation (via description) batch_6a080f6e218c8190b4c7b0d5de9f984c completed May 16, 2026, 6:32 a.m.
Created at: April 11, 2026, 3:36 p.m.