Triple

T1839108
Position Surface form Disambiguated ID Type / Status
Subject Inn E41132 entity
Predicate confluenceLocation P3421 FINISHED
Object Passau
Passau is a historic city in southeastern Germany, renowned for its picturesque old town and location at the meeting point of three rivers: the Danube, Inn, and Ilz.
 E412680 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: Passau | Statement: [Inn, confluenceLocation, Passau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Passau
Context triple: [Inn, confluenceLocation, Passau]
  • A. 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.
  • B. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • C. 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.
  • D. Traunstein
    Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
  • E. 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.
  • 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: Passau
Triple: [Inn, confluenceLocation, Passau]
Generated description
Passau is a historic city in southeastern Germany, renowned for its picturesque old town and location at the meeting point of three rivers: the Danube, Inn, and Ilz.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Passau
Target entity description: Passau is a historic city in southeastern Germany, renowned for its picturesque old town and location at the meeting point of three rivers: the Danube, Inn, and Ilz.
  • A. 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.
  • B. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • C. 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.
  • D. Traunstein
    Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
  • E. 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.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb03b3eb08190ae68d8476fc89c7f completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69b56b1a598c8190822f1d0cdd98fdbc completed March 14, 2026, 2:05 p.m.
NEDg Description generation batch_69b56bfa5a048190a2001d97d1664250 completed March 14, 2026, 2:08 p.m.
NED2 Entity disambiguation (via description) batch_69b56c7d7dac8190a9eced9fe7c4499a completed March 14, 2026, 2:11 p.m.
Created at: March 4, 2026, 7:33 p.m.