Triple

T12887123
Position Surface form Disambiguated ID Type / Status
Subject Darmstadt-Dieburg E308256 entity
Predicate contains P35 FINISHED
Object Groß-Umstadt
Groß-Umstadt is a historic small town in southern Hesse, Germany, known for its wine-growing tradition and medieval old town.
 E1011669 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: Groß-Umstadt | Statement: [Darmstadt-Dieburg, contains, Groß-Umstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Groß-Umstadt
Context triple: [Darmstadt-Dieburg, contains, Groß-Umstadt]
  • A. Großeibstadt
    Großeibstadt is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany, known for its rural character and Franconian village setting.
  • B. Schwalmstadt
    Schwalmstadt is a small town in the Schwalm-Eder district of northern Hesse, Germany, known for its historic half-timbered architecture and picturesque setting in the Schwalm River valley.
  • C. Höchheim
    Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
  • D. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • E. Obergum
    Obergum is a small neighborhood or former village that is now part of the town of Winsum in the province of Groningen, the Netherlands.
  • 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: Groß-Umstadt
Triple: [Darmstadt-Dieburg, contains, Groß-Umstadt]
Generated description
Groß-Umstadt is a historic small town in southern Hesse, Germany, known for its wine-growing tradition and medieval old town.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Groß-Umstadt
Target entity description: Groß-Umstadt is a historic small town in southern Hesse, Germany, known for its wine-growing tradition and medieval old town.
  • A. Großeibstadt
    Großeibstadt is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany, known for its rural character and Franconian village setting.
  • B. Schwalmstadt
    Schwalmstadt is a small town in the Schwalm-Eder district of northern Hesse, Germany, known for its historic half-timbered architecture and picturesque setting in the Schwalm River valley.
  • C. Höchheim
    Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
  • D. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • E. Obergum
    Obergum is a small neighborhood or former village that is now part of the town of Winsum in the province of Groningen, the Netherlands.
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9714415c08190aa9944b494a3ddad completed April 10, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af57a8b88190a3f15a3e9e02d492 completed May 3, 2026, 2:13 a.m.
NEDg Description generation batch_69f6b0cb53848190a7aa38f38d20e44d completed May 3, 2026, 2:19 a.m.
NED2 Entity disambiguation (via description) batch_69f6b1a539148190be7a4f16f738ca90 completed May 3, 2026, 2:23 a.m.
Created at: April 9, 2026, 5:39 p.m.