Triple

T25367770
Position Surface form Disambiguated ID Type / Status
Subject Wartburg, Tennessee E632848 entity
Predicate namedAfter P63 FINISHED
Object Wartburg, Germany
Wartburg, Germany is a historic town in the state of Thuringia best known for the nearby Wartburg Castle, a UNESCO World Heritage Site where Martin Luther translated the New Testament into German.
E1676101 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: Wartburg, Germany | Statement: [Wartburg, Tennessee, namedAfter, Wartburg, Germany]
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: Wartburg, Germany
Triple: [Wartburg, Tennessee, namedAfter, Wartburg, Germany]
Generated description
Wartburg, Germany is a historic town in the state of Thuringia best known for the nearby Wartburg Castle, a UNESCO World Heritage Site where Martin Luther translated the New Testament into German.

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_69e75a90c0dc819092f928b6ea0ecc72 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f4a10fcebc8190abea11247d65a276 completed May 1, 2026, 12:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a107605ca008190881b887efef07810 completed May 22, 2026, 3:28 p.m.
NEDg Description generation batch_6a10771a5a648190844a509e6ac507be completed May 22, 2026, 3:32 p.m.
NED2 Entity disambiguation (via description) batch_6a1077d01fa08190b5439eba879538ef completed May 22, 2026, 3:35 p.m.
Created at: April 21, 2026, 1:37 p.m.