Triple

T30711222
Position Surface form Disambiguated ID Type / Status
Subject Opel-Zoo E781897 entity
Predicate foundedBy P104 FINISHED
Object Georg von Opel
Georg von Opel was a German industrialist and philanthropist from the Opel automotive family, known for his contributions to business and the establishment of cultural and zoological institutions.
E1928558 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: Georg von Opel | Statement: [Opel-Zoo, foundedBy, Georg von Opel]
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: Georg von Opel
Triple: [Opel-Zoo, foundedBy, Georg von Opel]
Generated description
Georg von Opel was a German industrialist and philanthropist from the Opel automotive family, known for his contributions to business and the establishment of cultural and zoological institutions.

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_69f224abfcf081909492e64d3cc35262 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68c1efe608190a382d57a3aa3f542 completed May 2, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2899015b008190b6c34fe59a901f3c completed June 9, 2026, 10:51 p.m.
NEDg Description generation batch_6a289ab8b9c881908958b0824a1990c7 completed June 9, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_6a289b39ce9c8190a342e61537c2f11f completed June 9, 2026, 11:01 p.m.
Created at: April 29, 2026, 8:35 p.m.