Triple

T810865
Position Surface form Disambiguated ID Type / Status
Subject Middle Franconia E17540 entity
Predicate hasMajorRiver P165 FINISHED
Object Regnitz
The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
 E124915 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: Regnitz | Statement: [Middle Franconia, hasMajorRiver, Regnitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Regnitz
Context triple: [Middle Franconia, hasMajorRiver, Regnitz]
  • A. Saale
    The Saale is a major river in central Germany that flows through the states of Thuringia, Saxony-Anhalt, and Bavaria before joining the Elbe.
  • B. Neckar
    The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
  • C. Kinzig
    The Kinzig is a river in southwestern Germany that flows through the Black Forest region before joining the Rhine.
  • D. Werra
    The Werra is a major river in central Germany that forms one of the two headstreams of the Weser.
  • E. Elbe
    The Elbe is one of Central Europe's major rivers, flowing from the Czech Republic through Germany to the North Sea and serving as an important waterway for transport, industry, and agriculture.
  • 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: Regnitz
Triple: [Middle Franconia, hasMajorRiver, Regnitz]
Generated description
The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Regnitz
Target entity description: The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
  • A. Saale
    The Saale is a major river in central Germany that flows through the states of Thuringia, Saxony-Anhalt, and Bavaria before joining the Elbe.
  • B. Neckar
    The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
  • C. Kinzig
    The Kinzig is a river in southwestern Germany that flows through the Black Forest region before joining the Rhine.
  • D. Werra
    The Werra is a major river in central Germany that forms one of the two headstreams of the Weser.
  • E. Elbe
    The Elbe is one of Central Europe's major rivers, flowing from the Czech Republic through Germany to the North Sea and serving as an important waterway for transport, industry, and agriculture.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab282fe48190a05ee97550843cd7 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac427da0348190a8ae16db2a048d0b completed March 7, 2026, 3:21 p.m.
NEDg Description generation batch_69ac431f9ebc81908bcc9b259b2e47a8 completed March 7, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_69ac43a2a294819095cf58c39118389f completed March 7, 2026, 3:26 p.m.
Created at: March 1, 2026, 7:38 p.m.