Triple

T37360952
Position Surface form Disambiguated ID Type / Status
Subject FC Groningen E927574 entity
Predicate hasFormerCoach P4378 FINISHED
Object Ron Jans
Ron Jans is a Dutch football manager and former player best known for his long and successful coaching career in the Eredivisie.
E2225856 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: Ron Jans | Statement: [FC Groningen, hasFormerCoach, Ron Jans]
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: Ron Jans
Triple: [FC Groningen, hasFormerCoach, Ron Jans]
Generated description
Ron Jans is a Dutch football manager and former player best known for his long and successful coaching career in the Eredivisie.

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_69f76eb701788190b40824bc4594d985 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5befa82c8190ac214a049a0ae1ce completed May 6, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4076f2ccb4819083a18b8072981c36 completed June 28, 2026, 1:20 a.m.
NEDg Description generation batch_6a4079884de4819083aa67b9c5c9adf6 completed June 28, 2026, 1:31 a.m.
NED2 Entity disambiguation (via description) batch_6a4079df8aac8190b123ea92b559c196 completed June 28, 2026, 1:33 a.m.
Created at: May 3, 2026, 4:16 p.m.