Triple

T12406350
Position Surface form Disambiguated ID Type / Status
Subject Werra-Meißner-Kreis E296396 entity
Predicate containsMunicipality P852 FINISHED
Object Ringgau
Ringgau is a rural municipality in the Werra-Meißner district of northeastern Hesse, Germany, known for its scenic low mountain landscape near the Thuringian border.
E981110 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: Ringgau | Statement: [Werra-Meißner-Kreis, containsMunicipality, Ringgau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ringgau
Context triple: [Werra-Meißner-Kreis, containsMunicipality, Ringgau]
  • A. Dungun
    Dungun is a coastal town in the state of Terengganu, Malaysia, known historically for fishing and nearby iron ore mining activities.
  • B. Temerloh
    Temerloh is a town in central Pahang, Malaysia, known as a regional commercial hub and gateway to the state's interior.
  • C. Ratekau
    Ratekau is a municipality in the district of Ostholstein in Schleswig-Holstein, northern Germany, near the Baltic Sea coast.
  • D. Kuala Kangsar
    Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
  • E. Kuala Klawang
    Kuala Klawang is a small town in Negeri Sembilan, Malaysia, known as the main administrative and commercial center of the surrounding Jelebu area.
  • 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: Ringgau
Triple: [Werra-Meißner-Kreis, containsMunicipality, Ringgau]
Generated description
Ringgau is a rural municipality in the Werra-Meißner district of northeastern Hesse, Germany, known for its scenic low mountain landscape near the Thuringian border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ringgau
Target entity description: Ringgau is a rural municipality in the Werra-Meißner district of northeastern Hesse, Germany, known for its scenic low mountain landscape near the Thuringian border.
  • A. Dungun
    Dungun is a coastal town in the state of Terengganu, Malaysia, known historically for fishing and nearby iron ore mining activities.
  • B. Temerloh
    Temerloh is a town in central Pahang, Malaysia, known as a regional commercial hub and gateway to the state's interior.
  • C. Ratekau
    Ratekau is a municipality in the district of Ostholstein in Schleswig-Holstein, northern Germany, near the Baltic Sea coast.
  • D. Kuala Kangsar
    Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
  • E. Kuala Klawang
    Kuala Klawang is a small town in Negeri Sembilan, Malaysia, known as the main administrative and commercial center of the surrounding Jelebu area.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d48f1908190918551c794f98fe3 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63488cac08190a81b2151c827932e completed May 2, 2026, 5:29 p.m.
NEDg Description generation batch_69f635997b088190b6207fcac5594eb2 completed May 2, 2026, 5:34 p.m.
NED2 Entity disambiguation (via description) batch_69f636d9e13881908d3d08c6cf954304 completed May 2, 2026, 5:39 p.m.
Created at: April 8, 2026, 9:55 p.m.