Triple

T26883519
Position Surface form Disambiguated ID Type / Status
Subject Walther von der Vogelweide E676977 entity
Predicate contemporaryOf P6401 FINISHED
Object Hartmann von Aue
Hartmann von Aue was a prominent Middle High German poet and knight, known for his courtly epics and religious narratives that helped shape medieval German literature.
E1748038 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: Hartmann von Aue | Statement: [Walther von der Vogelweide, contemporaryOf, Hartmann von Aue]
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: Hartmann von Aue
Triple: [Walther von der Vogelweide, contemporaryOf, Hartmann von Aue]
Generated description
Hartmann von Aue was a prominent Middle High German poet and knight, known for his courtly epics and religious narratives that helped shape medieval German literature.

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_69eee9bc0c90819085608c8bdc513a57 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61f61446081909547ecbf78cf3bfc completed May 2, 2026, 3:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e9dcc5081908d4bd2ee88802ed6 completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a121f3c0dfc81908768b2670cb24b20 completed May 23, 2026, 9:42 p.m.
NED2 Entity disambiguation (via description) batch_6a1220284ddc819085b3ca2cad3fbfa9 completed May 23, 2026, 9:46 p.m.
Created at: April 27, 2026, 5:40 a.m.