Triple

T4285997
Position Surface form Disambiguated ID Type / Status
Subject Kendal E97268 entity
Predicate twinnedWith P1072 FINISHED
Object Rinteln
Rinteln is a historic town in Lower Saxony, Germany, situated on the River Weser and known for its well-preserved medieval architecture.
E427772 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: Rinteln | Statement: [Kendal, twinnedWith, Rinteln]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rinteln
Context triple: [Kendal, twinnedWith, Rinteln]
  • A. Rheinhausen
    Rheinhausen is a district of the German city of Duisburg, located on the western bank of the Rhine in North Rhine-Westphalia.
  • B. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • C. Neudorf
    Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
  • D. Wippingen
    Wippingen is a village and district (Ortsteil) of the municipality of Blaustein in the Alb-Donau district of Baden-Württemberg, Germany.
  • E. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • 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: Rinteln
Triple: [Kendal, twinnedWith, Rinteln]
Generated description
Rinteln is a historic town in Lower Saxony, Germany, situated on the River Weser and known for its well-preserved medieval architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rinteln
Target entity description: Rinteln is a historic town in Lower Saxony, Germany, situated on the River Weser and known for its well-preserved medieval architecture.
  • A. Rheinhausen
    Rheinhausen is a district of the German city of Duisburg, located on the western bank of the Rhine in North Rhine-Westphalia.
  • B. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • C. Neudorf
    Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
  • D. Wippingen
    Wippingen is a village and district (Ortsteil) of the municipality of Blaustein in the Alb-Donau district of Baden-Württemberg, Germany.
  • E. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3505d23d88190a638f2cc2acee9ee completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7c657b08190b96135c34622e559 completed March 14, 2026, 7:32 p.m.
NEDg Description generation batch_69b5bba7859481909e2afe21774dc599 completed March 14, 2026, 7:48 p.m.
NED2 Entity disambiguation (via description) batch_69b5bc5f26508190b333ec09c517f7c8 completed March 14, 2026, 7:51 p.m.
Created at: March 12, 2026, 11:07 p.m.