Triple

T24199065
Position Surface form Disambiguated ID Type / Status
Subject Volkach E599919 entity
Predicate hasSubdivision P747 FINISHED
Object Fahr
Fahr is a district of the Franconian town of Volkach in Bavaria, Germany, known for its winegrowing and picturesque location along the Main River.
E1623258 NE FINISHED

How this triple was built (2 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: Fahr | Statement: [Volkach, hasSubdivision, Fahr]
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: Fahr
Triple: [Volkach, hasSubdivision, Fahr]
Generated description
Fahr is a district of the Franconian town of Volkach in Bavaria, Germany, known for its winegrowing and picturesque location along the Main River.

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_69e288ceaab88190899d0acb5931591d completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f27c9f61f881909f7e1287388ff982 completed April 29, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd133c74819086de74e890829b13 completed May 22, 2026, 2:18 a.m.
NEDg Description generation batch_6a0fbdc918dc8190bb677ebca13ec033 completed May 22, 2026, 2:22 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbe63971c81908ab3e446da49765d completed May 22, 2026, 2:24 a.m.
Created at: April 17, 2026, 11:36 p.m.