Triple

T8797588
Position Surface form Disambiguated ID Type / Status
Subject Schmitten E209326 entity
Predicate hasSubdivision P747 FINISHED
Object Seelenberg
Seelenberg is a small village that forms one of the local subdivisions of the municipality of Schmitten in Germany.
E759637 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: Seelenberg | Statement: [Schmitten, hasSubdivision, Seelenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seelenberg
Context triple: [Schmitten, hasSubdivision, Seelenberg]
  • A. Wurmberg
    Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
  • B. Sedelsberg
    Sedelsberg is a village in the municipality of Saterland in Lower Saxony, Germany.
  • C. Schellenberg
    Schellenberg is a small municipality in Liechtenstein known for its historic sites and scenic Alpine surroundings.
  • D. Seckbach
    Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
  • E. Suhre
    The Suhre is a river in Switzerland that flows through the cantons of Lucerne and Aargau before joining the Aare.
  • 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: Seelenberg
Triple: [Schmitten, hasSubdivision, Seelenberg]
Generated description
Seelenberg is a small village that forms one of the local subdivisions of the municipality of Schmitten in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Seelenberg
Target entity description: Seelenberg is a small village that forms one of the local subdivisions of the municipality of Schmitten in Germany.
  • A. Wurmberg
    Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
  • B. Sedelsberg
    Sedelsberg is a village in the municipality of Saterland in Lower Saxony, Germany.
  • C. Schellenberg
    Schellenberg is a small municipality in Liechtenstein known for its historic sites and scenic Alpine surroundings.
  • D. Seckbach
    Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
  • E. Suhre
    The Suhre is a river in Switzerland that flows through the cantons of Lucerne and Aargau before joining the Aare.
  • 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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa370d08190885ef65e3a3e56d3 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f5d655881909013ac3e2ac0cebb completed April 3, 2026, 7:42 a.m.
NEDg Description generation batch_69cf71c118848190a937ecf714556ef3 completed April 3, 2026, 7:52 a.m.
NED2 Entity disambiguation (via description) batch_69cf744b17e88190b14607e6dff823a3 completed April 3, 2026, 8:03 a.m.
Created at: March 30, 2026, 6:44 p.m.