Triple

T3381505
Position Surface form Disambiguated ID Type / Status
Subject Wedding E71194 entity
Predicate hasLandmark P105 FINISHED
Object Sprengelkiez
Sprengelkiez is a residential neighborhood in Berlin’s Wedding district known for its canalside location, historic buildings, and vibrant local community.
 E353651 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: Sprengelkiez | Statement: [Wedding, hasLandmark, Sprengelkiez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sprengelkiez
Context triple: [Wedding, hasLandmark, Sprengelkiez]
  • A. Schievelbein
    Schievelbein is a historic town in Pomerania, now known as Świdwin in northwestern Poland.
  • B. Bowlegs
    Bowlegs was a prominent Seminole leader and war chief known for resisting U.S. expansion during the early 19th-century Seminole conflicts in Florida.
  • C. Skolio
    Skolio is one of the principal summits of Greece’s Mount Olympus, known as its second-highest peak.
  • D. Pavlik
    Pavlik is a diminutive Slavic given name, commonly used as an affectionate or informal form of Pavel.
  • E. Kyllopodion
    Kyllopodion is an epithet of the Greek god Hephaestus that highlights his lameness or crippled foot.
  • 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: Sprengelkiez
Triple: [Wedding, hasLandmark, Sprengelkiez]
Generated description
Sprengelkiez is a residential neighborhood in Berlin’s Wedding district known for its canalside location, historic buildings, and vibrant local community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sprengelkiez
Target entity description: Sprengelkiez is a residential neighborhood in Berlin’s Wedding district known for its canalside location, historic buildings, and vibrant local community.
  • A. Schievelbein
    Schievelbein is a historic town in Pomerania, now known as Świdwin in northwestern Poland.
  • B. Bowlegs
    Bowlegs was a prominent Seminole leader and war chief known for resisting U.S. expansion during the early 19th-century Seminole conflicts in Florida.
  • C. Skolio
    Skolio is one of the principal summits of Greece’s Mount Olympus, known as its second-highest peak.
  • D. Pavlik
    Pavlik is a diminutive Slavic given name, commonly used as an affectionate or informal form of Pavel.
  • E. Kyllopodion
    Kyllopodion is an epithet of the Greek god Hephaestus that highlights his lameness or crippled foot.
  • 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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb5e9af608190bfb228ef99a87bb7 completed March 8, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3344f9b448190aab1038ead60fa48 completed March 12, 2026, 9:46 p.m.
NEDg Description generation batch_69b338147cc0819095f00b28910e178a completed March 12, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_69b338967c6c819090fe5f77bfa1978f completed March 12, 2026, 10:05 p.m.
Created at: March 8, 2026, 3:14 p.m.