Triple

T657507
Position Surface form Disambiguated ID Type / Status
Subject Lichtenfels E11679 entity
Predicate hasSubdivision P747 FINISHED
Object Seubelsdorf
Seubelsdorf is a village that forms one of the local subdivisions of the town of Lichtenfels in Bavaria, Germany.
 E100694 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: Seubelsdorf | Statement: [Lichtenfels, hasSubdivision, Seubelsdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Seubelsdorf
Context triple: [Lichtenfels, hasSubdivision, Seubelsdorf]
  • A. Hermsdorf
    Hermsdorf is a residential locality in the Berlin borough of Reinickendorf, known for its green surroundings and village-like character on the city’s northern edge.
  • B. Ronsdorf
    Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
  • C. Alt-Mariendorf
    Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
  • D. Reundorf
    Reundorf is a village-level subdivision of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
  • E. Schöneberg
    Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
  • 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: Seubelsdorf
Triple: [Lichtenfels, hasSubdivision, Seubelsdorf]
Generated description
Seubelsdorf is a village that forms one of the local subdivisions of the town of Lichtenfels in Bavaria, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Seubelsdorf
Target entity description: Seubelsdorf is a village that forms one of the local subdivisions of the town of Lichtenfels in Bavaria, Germany.
  • A. Hermsdorf
    Hermsdorf is a residential locality in the Berlin borough of Reinickendorf, known for its green surroundings and village-like character on the city’s northern edge.
  • B. Ronsdorf
    Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
  • C. Alt-Mariendorf
    Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
  • D. Reundorf
    Reundorf is a village-level subdivision of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
  • E. Schöneberg
    Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
  • 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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49fa55e048190bd9913c6c31772d0 completed March 1, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7927c75448190aafcaa955519833c completed March 4, 2026, 2:01 a.m.
NEDg Description generation batch_69a7965d1ce08190a1b6b30ffa23f974 completed March 4, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69a796b5cf708190ac3d11f80a3af7ce completed March 4, 2026, 2:19 a.m.
Created at: March 1, 2026, 7:36 p.m.