Triple

T29532169
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen Type 2 E749235 entity
Predicate designer P184 FINISHED
Object Ben Pon
Ben Pon was a Dutch businessman and automobile importer credited with inspiring the design of the iconic Volkswagen Type 2 microbus.
E1872078 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: Ben Pon | Statement: [Volkswagen Type 2, designer, Ben Pon]
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: Ben Pon
Triple: [Volkswagen Type 2, designer, Ben Pon]
Generated description
Ben Pon was a Dutch businessman and automobile importer credited with inspiring the design of the iconic Volkswagen Type 2 microbus.

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_69f0bd47abb081909bd6e6a33d770fd8 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66cc3679c8190be65a057a4c6502d completed May 2, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260c366fa8819085ec36e542b9469f completed June 8, 2026, 12:26 a.m.
NEDg Description generation batch_6a2611d63328819086c5a27ccf3586eb completed June 8, 2026, 12:50 a.m.
NED2 Entity disambiguation (via description) batch_6a2615faed10819083662734f71731ae completed June 8, 2026, 1:08 a.m.
Created at: April 28, 2026, 4:54 p.m.