Triple

T9859012
Position Surface form Disambiguated ID Type / Status
Subject Coburg district E239658 entity
Predicate contains P35 FINISHED
Object Itzgrund
Itzgrund is a small municipality in the Bavarian region of Germany, known for its rural character and location in the valley of the Itz River.
 E825759 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: Itzgrund | Statement: [Coburg district, contains, Itzgrund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Itzgrund
Context triple: [Coburg district, contains, Itzgrund]
  • A. Ittigen
    Ittigen is a municipality in the canton of Bern in Switzerland that functions largely as a suburban community within the greater Bern urban region.
  • B. Witellikon
    Witellikon is a small settlement within the municipality of Küsnacht in the canton of Zürich, Switzerland, situated along the shores of Lake Zurich.
  • C. Zihl
    Zihl is a river in Switzerland that serves as a key tributary within the Aare river system.
  • D. Taborio
    Taborio is a village settlement located on the island of Nonouti in the Republic of Kiribati.
  • E. Karesi
    Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
  • 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: Itzgrund
Triple: [Coburg district, contains, Itzgrund]
Generated description
Itzgrund is a small municipality in the Bavarian region of Germany, known for its rural character and location in the valley of the Itz River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Itzgrund
Target entity description: Itzgrund is a small municipality in the Bavarian region of Germany, known for its rural character and location in the valley of the Itz River.
  • A. Ittigen
    Ittigen is a municipality in the canton of Bern in Switzerland that functions largely as a suburban community within the greater Bern urban region.
  • B. Witellikon
    Witellikon is a small settlement within the municipality of Küsnacht in the canton of Zürich, Switzerland, situated along the shores of Lake Zurich.
  • C. Zihl
    Zihl is a river in Switzerland that serves as a key tributary within the Aare river system.
  • D. Taborio
    Taborio is a village settlement located on the island of Nonouti in the Republic of Kiribati.
  • E. Karesi
    Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb39b06b48190ab53ff00ff0513ca completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e43b2de881909e00f6701d1c7b54 completed April 5, 2026, 4:25 a.m.
NEDg Description generation batch_69d1e5204f748190b1f56ee5469828a2 completed April 5, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_69d1e598243481909278cb3c911ce3db completed April 5, 2026, 4:31 a.m.
Created at: March 30, 2026, 8:35 p.m.