Triple

T38522224
Position Surface form Disambiguated ID Type / Status
Subject Neuenstein E922512 entity
Predicate hasLandmark P105 FINISHED
Object Neuenstein Castle
Neuenstein Castle is a historic hilltop fortress in Neuenstein, Germany, known for its well-preserved Renaissance architecture and role as a former residence of regional nobility.
E2282273 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: Neuenstein Castle | Statement: [Neuenstein, hasLandmark, Neuenstein Castle]
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: Neuenstein Castle
Triple: [Neuenstein, hasLandmark, Neuenstein Castle]
Generated description
Neuenstein Castle is a historic hilltop fortress in Neuenstein, Germany, known for its well-preserved Renaissance architecture and role as a former residence of regional nobility.

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_69f76ea5f5588190bd0b28c82e975640 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd2952a548190960fc56d8388a838 completed May 7, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a421581a0d48190a32d948c4d3a1888 completed June 29, 2026, 6:49 a.m.
NEDg Description generation batch_6a42168f46ec8190888fddb8600dc063 completed June 29, 2026, 6:54 a.m.
NED2 Entity disambiguation (via description) batch_6a4217206b508190ba1b578872c6b579 completed June 29, 2026, 6:56 a.m.
Created at: May 3, 2026, 4:32 p.m.