Triple

T18846907
Position Surface form Disambiguated ID Type / Status
Subject Amt Hohe Elbgeest E460939 entity
Predicate hasMunicipality P847 FINISHED
Object Artlenburg
Artlenburg is a small municipality in northern Germany, situated on the Elbe River in the state of Lower Saxony.
E1345341 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: Artlenburg | Statement: [Amt Hohe Elbgeest, hasMunicipality, Artlenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Artlenburg
Context triple: [Amt Hohe Elbgeest, hasMunicipality, Artlenburg]
  • A. Altburg
    Altburg is a village-sized district of the town of Calw in the state of Baden-Württemberg in southwestern Germany.
  • B. Arzdorf
    Arzdorf is a village and district of the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • C. Hachenburg
    Hachenburg is a historic small town in the Westerwald region of Rhineland-Palatinate, Germany, known for its medieval town center and hilltop castle.
  • D. Offenberg
    Offenberg is a municipality in the Bavarian region of Germany, situated within the Regen district.
  • E. Berlinghausen
    Berlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, 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: Artlenburg
Triple: [Amt Hohe Elbgeest, hasMunicipality, Artlenburg]
Generated description
Artlenburg is a small municipality in northern Germany, situated on the Elbe River in the state of Lower Saxony.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Artlenburg
Target entity description: Artlenburg is a small municipality in northern Germany, situated on the Elbe River in the state of Lower Saxony.
  • A. Altburg
    Altburg is a village-sized district of the town of Calw in the state of Baden-Württemberg in southwestern Germany.
  • B. Arzdorf
    Arzdorf is a village and district of the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • C. Hachenburg
    Hachenburg is a historic small town in the Westerwald region of Rhineland-Palatinate, Germany, known for its medieval town center and hilltop castle.
  • D. Offenberg
    Offenberg is a municipality in the Bavarian region of Germany, situated within the Regen district.
  • E. Berlinghausen
    Berlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, 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_69d8dcfa11e4819090ab1ef5bdcd2b2e completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5b8efafdc81909608b8a47deeaa8e completed April 20, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0567743f788190b85a9fa1e7345a27 completed May 14, 2026, 6:11 a.m.
NEDg Description generation batch_6a0568fc78748190b487d4c0b444a8ea completed May 14, 2026, 6:17 a.m.
NED2 Entity disambiguation (via description) batch_6a056966665c81909d9e82f1fbd1d518 completed May 14, 2026, 6:19 a.m.
Created at: April 10, 2026, 11:56 a.m.