Triple

T5301136
Position Surface form Disambiguated ID Type / Status
Subject Ortenaukreis E119983 entity
Predicate containsMunicipality P852 FINISHED
Object Willstätt
Willstätt is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine and the French border.
E527155 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: Willstätt | Statement: [Ortenaukreis, containsMunicipality, Willstätt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Willstätt
Context triple: [Ortenaukreis, containsMunicipality, Willstätt]
  • A. Taufkirchen
    Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
  • B. Hettstadt
    Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
  • C. Altötting
    Altötting is a Bavarian pilgrimage town renowned as one of Germany’s most important Catholic shrines, centered around the Chapel of Grace and its venerated Black Madonna.
  • D. Dischingen
    Dischingen is a small municipality in the state of Baden-Württemberg in southern Germany, known for its rural character and location within the Swabian Jura region.
  • E. Kirchlindach
    Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
  • 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: Willstätt
Triple: [Ortenaukreis, containsMunicipality, Willstätt]
Generated description
Willstätt is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine and the French border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Willstätt
Target entity description: Willstätt is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine and the French border.
  • A. Taufkirchen
    Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
  • B. Hettstadt
    Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
  • C. Altötting
    Altötting is a Bavarian pilgrimage town renowned as one of Germany’s most important Catholic shrines, centered around the Chapel of Grace and its venerated Black Madonna.
  • D. Dischingen
    Dischingen is a small municipality in the state of Baden-Württemberg in southern Germany, known for its rural character and location within the Swabian Jura region.
  • E. Kirchlindach
    Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
  • 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_69bd44704be88190acdb2ac481b0ff55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd8509f67c8190b2f82a8370301a59 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfdb16987481909c84c219d866815a completed March 22, 2026, 12:05 p.m.
NEDg Description generation batch_69bfdbc5174481908928362a758a0b5e completed March 22, 2026, 12:08 p.m.
NED2 Entity disambiguation (via description) batch_69bfdc185b0c81909e186194b1e67e43 completed March 22, 2026, 12:10 p.m.
Created at: March 20, 2026, 1:53 p.m.