Triple

T16460192
Position Surface form Disambiguated ID Type / Status
Subject Bolligen E399785 entity
Predicate hasLocality P7943 FINISHED
Object Ferenberg
Ferenberg is a small locality within the municipality of Bolligen in the canton of Bern, Switzerland.
E1220685 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: Ferenberg | Statement: [Bolligen, hasLocality, Ferenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ferenberg
Context triple: [Bolligen, hasLocality, Ferenberg]
  • A. Sennfeld
    Sennfeld is a municipality in the Schweinfurt district of Bavaria, Germany, known for its traditional Franconian character and proximity to the city of Schweinfurt.
  • B. Freyburg
    Freyburg is a historic town in the German state of Saxony-Anhalt, renowned for its wine production and medieval architecture.
  • C. Todenfeld
    Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • D. Valdorf
    Valdorf is a district or locality within the town of Vlotho in the German state of North Rhine-Westphalia.
  • E. Pennenfeld
    Pennenfeld is a residential subdistrict of the Bonn borough of Bad Godesberg in 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: Ferenberg
Triple: [Bolligen, hasLocality, Ferenberg]
Generated description
Ferenberg is a small locality within the municipality of Bolligen in the canton of Bern, Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ferenberg
Target entity description: Ferenberg is a small locality within the municipality of Bolligen in the canton of Bern, Switzerland.
  • A. Sennfeld
    Sennfeld is a municipality in the Schweinfurt district of Bavaria, Germany, known for its traditional Franconian character and proximity to the city of Schweinfurt.
  • B. Freyburg
    Freyburg is a historic town in the German state of Saxony-Anhalt, renowned for its wine production and medieval architecture.
  • C. Todenfeld
    Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • D. Valdorf
    Valdorf is a district or locality within the town of Vlotho in the German state of North Rhine-Westphalia.
  • E. Pennenfeld
    Pennenfeld is a residential subdistrict of the Bonn borough of Bad Godesberg in 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d80e66c8190b2b3199efe9cfaa1 completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ed25bcc819090ccca4705e4e24f completed May 10, 2026, 11:41 a.m.
NEDg Description generation batch_6a006f9043b8819086143b2ec0cf1657 completed May 10, 2026, 11:44 a.m.
NED2 Entity disambiguation (via description) batch_6a00701fc1848190b3248a70b462eab1 completed May 10, 2026, 11:46 a.m.
Created at: April 10, 2026, 5:10 a.m.