Triple

T1091702
Position Surface form Disambiguated ID Type / Status
Subject Technical University of Munich E24177 entity
Predicate campus P269 FINISHED
Object Straubing
Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
 E269369 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: Straubing | Statement: [Technical University of Munich, campus, Straubing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Straubing
Context triple: [Technical University of Munich, campus, Straubing]
  • A. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • B. Kempten
    Kempten is a historic town in Bavaria, Germany, considered one of the country’s oldest urban settlements and known for its location in the Allgäu region.
  • C. Forchheim
    Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
  • D. Amberg
    Amberg is a historic town in Bavaria, Germany, known for its well-preserved medieval old town and former role as a regional administrative and trading center.
  • E. Bamberg
    Bamberg is a historic city in northern Bavaria, Germany, renowned for its well-preserved medieval old town and status as a UNESCO World Heritage Site.
  • 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: Straubing
Triple: [Technical University of Munich, campus, Straubing]
Generated description
Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Straubing
Target entity description: Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
  • A. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • B. Kempten
    Kempten is a historic town in Bavaria, Germany, considered one of the country’s oldest urban settlements and known for its location in the Allgäu region.
  • C. Forchheim
    Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
  • D. Amberg
    Amberg is a historic town in Bavaria, Germany, known for its well-preserved medieval old town and former role as a regional administrative and trading center.
  • E. Bamberg
    Bamberg is a historic city in northern Bavaria, Germany, renowned for its well-preserved medieval old town and status as a UNESCO World Heritage Site.
  • 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b982018481908b222df095e318c0 completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69af1731ebe481908ffd1a670ae86286 completed March 9, 2026, 6:53 p.m.
NEDg Description generation batch_69af188b0dfc819085d3b923b204f03e completed March 9, 2026, 6:59 p.m.
NED2 Entity disambiguation (via description) batch_69af191a14348190851ee44d3dbc20e3 completed March 9, 2026, 7:01 p.m.
Created at: March 1, 2026, 7:42 p.m.