Triple

T31371637
Position Surface form Disambiguated ID Type / Status
Subject museum landscape of Frankfurt am Main E800177 entity
Predicate hasPart P35 FINISHED
Object Bibelhaus Erlebnis Museum
Bibelhaus Erlebnis Museum is an interactive museum in Frankfurt am Main that explores the history, cultural context, and stories of the Bible through hands-on exhibits and immersive experiences.
E209768 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: Bibelhaus Erlebnis Museum | Statement: [museum landscape of Frankfurt am Main, hasPart, Bibelhaus Erlebnis Museum]
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: Bibelhaus Erlebnis Museum
Triple: [museum landscape of Frankfurt am Main, hasPart, Bibelhaus Erlebnis Museum]
Generated description
Bibelhaus Erlebnis Museum is an interactive museum in Frankfurt am Main that explores the history, cultural context, and stories of the Bible through hands-on exhibits and immersive experiences.

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_69f224e6b7448190ac6bf97ad7364160 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f8a5d2c81908d4d0d43fc72966f completed May 3, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a722db15881908ebdc3e8826fb547 completed June 11, 2026, 8:30 a.m.
NEDg Description generation batch_6a2a7292e9b88190adb64e68cd524fa8 completed June 11, 2026, 8:32 a.m.
NED2 Entity disambiguation (via description) batch_6a2aa2b6da8c819096e0e740660c721f completed June 11, 2026, 11:57 a.m.
Created at: April 29, 2026, 9:18 p.m.