Triple

T16561009
Position Surface form Disambiguated ID Type / Status
Subject Kraichgau E402336 entity
Predicate contains P35 FINISHED
Object Östringen
Östringen is a small town in southwestern Germany’s Baden-Württemberg region, situated within the hilly, wine-producing landscape of the Kraichgau.
E1220138 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: Östringen | Statement: [Kraichgau, contains, Östringen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Östringen
Context triple: [Kraichgau, contains, Östringen]
  • A. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • B. Lindesberg
    Lindesberg is a small historic town in central Sweden known for its mining heritage and lakeside setting.
  • C. Strömholm
    Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
  • D. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • E. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • 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: Östringen
Triple: [Kraichgau, contains, Östringen]
Generated description
Östringen is a small town in southwestern Germany’s Baden-Württemberg region, situated within the hilly, wine-producing landscape of the Kraichgau.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Östringen
Target entity description: Östringen is a small town in southwestern Germany’s Baden-Württemberg region, situated within the hilly, wine-producing landscape of the Kraichgau.
  • A. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • B. Lindesberg
    Lindesberg is a small historic town in central Sweden known for its mining heritage and lakeside setting.
  • C. Strömholm
    Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
  • D. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • E. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3576d88288190b33543bea4706a36 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067be809c81909c93eb1253fbf8e5 completed May 10, 2026, 11:10 a.m.
NEDg Description generation batch_6a006a4c343481909bf56cad83f3ed81 completed May 10, 2026, 11:21 a.m.
NED2 Entity disambiguation (via description) batch_6a006afcbdb88190b34bfe6f4cc0fd40 completed May 10, 2026, 11:24 a.m.
Created at: April 10, 2026, 5:15 a.m.