Triple

T8922105
Position Surface form Disambiguated ID Type / Status
Subject Egling an der Paar E212445 entity
Predicate locatedOnRiver P165 FINISHED
Object Paar
Paar is a river in Bavaria, Germany, known for flowing through several towns and rural landscapes before joining the Danube.
 E765883 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: Paar | Statement: [Egling an der Paar, locatedOnRiver, Paar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paar
Context triple: [Egling an der Paar, locatedOnRiver, Paar]
  • A. Paar
    Paar is a surname most notably associated with American television host and comedian Jack Paar, a pioneering figure of late-night talk shows.
  • B. Paar
    "Paar" is a critically acclaimed Indian film directed by Goutam Ghose, known for its stark portrayal of social injustice and rural hardship.
  • C. Parainen
    Parainen is a coastal town and municipality in southwestern Finland known for its archipelago landscape and maritime heritage.
  • D. Dvoynik
    Dvoynik is the original Russian title of Fyodor Dostoevsky’s novella "The Double," a psychological work about a government clerk who encounters his uncanny doppelgänger.
  • E. Manche
    Manche is a coastal department in the Normandy region of northwestern France, known for its rugged shoreline along the English Channel and historic sites such as Mont-Saint-Michel.
  • 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: Paar
Triple: [Egling an der Paar, locatedOnRiver, Paar]
Generated description
Paar is a river in Bavaria, Germany, known for flowing through several towns and rural landscapes before joining the Danube.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paar
Target entity description: Paar is a river in Bavaria, Germany, known for flowing through several towns and rural landscapes before joining the Danube.
  • A. Paar
    Paar is a surname most notably associated with American television host and comedian Jack Paar, a pioneering figure of late-night talk shows.
  • B. Paar
    "Paar" is a critically acclaimed Indian film directed by Goutam Ghose, known for its stark portrayal of social injustice and rural hardship.
  • C. Parainen
    Parainen is a coastal town and municipality in southwestern Finland known for its archipelago landscape and maritime heritage.
  • D. Dvoynik
    Dvoynik is the original Russian title of Fyodor Dostoevsky’s novella "The Double," a psychological work about a government clerk who encounters his uncanny doppelgänger.
  • E. Manche
    Manche is a coastal department in the Normandy region of northwestern France, known for its rugged shoreline along the English Channel and historic sites such as Mont-Saint-Michel.
  • 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_69ca839481d48190b42b037e0d0f636c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc665143688190872c681f4299bd9f completed April 1, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba4f094c81909a30d3be640ac9e0 completed April 3, 2026, 1:02 p.m.
NEDg Description generation batch_69cfbb5fe4f48190bd86c7606b1993bc completed April 3, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_69cfbbcc6db8819080be0b2ae55837e2 completed April 3, 2026, 1:08 p.m.
Created at: March 30, 2026, 6:56 p.m.