Triple

T855132
Position Surface form Disambiguated ID Type / Status
Subject Głogów E18473 entity
Predicate hasTwinTown P919 FINISHED
Object Sommerda
Sommerda is a town in the German state of Thuringia, known for its industrial history and central location near the Unstrut River.
 E100965 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: Sommerda | Statement: [Głogów, hasTwinTown, Sommerda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sommerda
Context triple: [Głogów, hasTwinTown, Sommerda]
  • A. Blomstedt
    Blomstedt is a surname most prominently associated with Herbert Blomstedt, a renowned Swedish conductor known for his interpretations of the classical and romantic repertoire.
  • B. Odelsting
    The Odelsting was one of the two former chambers of the Norwegian Parliament, historically responsible for initiating and passing most legislation before Norway adopted a unicameral system.
  • C. Heden
    Heden is a central district in Gothenburg, Sweden, known for its sports facilities, event venues, and open recreational spaces.
  • D. Skaugum
    Skaugum is the official country residence of the Norwegian royal family, located in Asker near Oslo.
  • E. Selke
    The Selke is a river in central Germany that flows through the Harz Mountains and Saxony-Anhalt, known for its scenic valleys and historic towns along its course.
  • 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: Sommerda
Triple: [Głogów, hasTwinTown, Sommerda]
Generated description
Sommerda is a town in the German state of Thuringia, known for its industrial history and central location near the Unstrut River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sommerda
Target entity description: Sommerda is a town in the German state of Thuringia, known for its industrial history and central location near the Unstrut River.
  • A. Blomstedt
    Blomstedt is a surname most prominently associated with Herbert Blomstedt, a renowned Swedish conductor known for his interpretations of the classical and romantic repertoire.
  • B. Odelsting
    The Odelsting was one of the two former chambers of the Norwegian Parliament, historically responsible for initiating and passing most legislation before Norway adopted a unicameral system.
  • C. Heden
    Heden is a central district in Gothenburg, Sweden, known for its sports facilities, event venues, and open recreational spaces.
  • D. Skaugum
    Skaugum is the official country residence of the Norwegian royal family, located in Asker near Oslo.
  • E. Selke
    The Selke is a river in central Germany that flows through the Harz Mountains and Saxony-Anhalt, known for its scenic valleys and historic towns along its course.
  • 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_69a4938bdd3c8190a954a3c11844d9cf completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac3a48c08190b4677d825fcbfaf9 completed March 1, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3bfcf308190b1ffc63ccd32cc66 completed March 4, 2026, 3:15 a.m.
NEDg Description generation batch_69a7a4416144819099d6388fac05f475 completed March 4, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_69a7a4b346b88190a264742a3f6ab2d1 completed March 4, 2026, 3:19 a.m.
Created at: March 1, 2026, 7:39 p.m.