Triple

T8052987
Position Surface form Disambiguated ID Type / Status
Subject Bad Lauchstädt E187719 entity
Predicate hasFormerName P65 FINISHED
Object Lauchstädt
Lauchstädt is the former name of the German spa town now known as Bad Lauchstädt in the state of Saxony-Anhalt.
E722448 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: Lauchstädt | Statement: [Bad Lauchstädt, hasFormerName, Lauchstädt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauchstädt
Context triple: [Bad Lauchstädt, hasFormerName, Lauchstädt]
  • A. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • B. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • C. Stedesdorf
    Stedesdorf is a small municipality in Lower Saxony, Germany, situated in the East Frisian region.
  • D. Stühlingen
    Stühlingen is a small town in the state of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its scenic setting in the Black Forest region.
  • E. Burkhardtsdorf
    Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
  • 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: Lauchstädt
Triple: [Bad Lauchstädt, hasFormerName, Lauchstädt]
Generated description
Lauchstädt is the former name of the German spa town now known as Bad Lauchstädt in the state of Saxony-Anhalt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lauchstädt
Target entity description: Lauchstädt is the former name of the German spa town now known as Bad Lauchstädt in the state of Saxony-Anhalt.
  • A. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • B. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • C. Stedesdorf
    Stedesdorf is a small municipality in Lower Saxony, Germany, situated in the East Frisian region.
  • D. Stühlingen
    Stühlingen is a small town in the state of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its scenic setting in the Black Forest region.
  • E. Burkhardtsdorf
    Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
  • 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_69ca82b15e948190a62fd7af5218426a completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f7c425c8190aa1b2f534afeb58c completed March 31, 2026, 3:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd6759e83c8190869732f955279cee completed April 1, 2026, 6:43 p.m.
NEDg Description generation batch_69cd6d4fa17481909f28ad7eb9bceb42 completed April 1, 2026, 7:09 p.m.
NED2 Entity disambiguation (via description) batch_69cd7da4f3a0819080eed3d03c293789 completed April 1, 2026, 8:18 p.m.
Created at: March 30, 2026, 5:25 p.m.