Triple

T8977736
Position Surface form Disambiguated ID Type / Status
Subject Muttenz E214435 entity
Predicate hasTwinTown P919 FINISHED
Object Krailling
Krailling is a municipality in the district of Starnberg in Bavaria, Germany, known as a residential community within the Munich metropolitan area.
E773040 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: Krailling | Statement: [Muttenz, hasTwinTown, Krailling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krailling
Context triple: [Muttenz, hasTwinTown, Krailling]
  • A. Vöcklabruck
    Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
  • B. Lustenau
    Lustenau is a large market town in the Austrian state of Vorarlberg, known for its location on the Rhine near the Swiss border and its strong textile industry heritage.
  • C. Leoben
    Leoben is a historic industrial and university city in the Austrian state of Styria, known especially for its steel industry and mining university.
  • D. Schärding
    Schärding is a historic Austrian town on the border with Germany, known for its well-preserved baroque old town and riverside setting.
  • E. Grödig
    Grödig is a municipality in the Austrian state of Salzburg, located just south of the city of Salzburg near the Untersberg mountain.
  • 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: Krailling
Triple: [Muttenz, hasTwinTown, Krailling]
Generated description
Krailling is a municipality in the district of Starnberg in Bavaria, Germany, known as a residential community within the Munich metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Krailling
Target entity description: Krailling is a municipality in the district of Starnberg in Bavaria, Germany, known as a residential community within the Munich metropolitan area.
  • A. Vöcklabruck
    Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
  • B. Lustenau
    Lustenau is a large market town in the Austrian state of Vorarlberg, known for its location on the Rhine near the Swiss border and its strong textile industry heritage.
  • C. Leoben
    Leoben is a historic industrial and university city in the Austrian state of Styria, known especially for its steel industry and mining university.
  • D. Schärding
    Schärding is a historic Austrian town on the border with Germany, known for its well-preserved baroque old town and riverside setting.
  • E. Grödig
    Grödig is a municipality in the Austrian state of Salzburg, located just south of the city of Salzburg near the Untersberg mountain.
  • 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_69ca839ea8b88190922c6a326ffcc0d3 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc67a33c8481909125acf4b7f0a919 completed April 1, 2026, 12:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb8de5e081909cce650a0b299e85 completed April 3, 2026, 3:23 p.m.
NEDg Description generation batch_69cfdcae0e5c81909c50a0b53c1cf7cc completed April 3, 2026, 3:28 p.m.
NED2 Entity disambiguation (via description) batch_69cfdd6a2ba481908d66fed8f05a1297 completed April 3, 2026, 3:31 p.m.
Created at: March 30, 2026, 7:02 p.m.