Triple

T35380054
Position Surface form Disambiguated ID Type / Status
Subject Boulevard Charlemagne / Karel de Grote-laan E1022619 entity
Predicate hasNameInDutch P13254 FINISHED
Object Karel de Grote-laan
Karel de Grote-laan is the Dutch name for a major Brussels thoroughfare named after Charlemagne, running through the European Quarter near key EU institutions.
E2138835 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: Karel de Grote-laan | Statement: [Boulevard Charlemagne / Karel de Grote-laan, hasNameInDutch, Karel de Grote-laan]
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: Karel de Grote-laan
Triple: [Boulevard Charlemagne / Karel de Grote-laan, hasNameInDutch, Karel de Grote-laan]
Generated description
Karel de Grote-laan is the Dutch name for a major Brussels thoroughfare named after Charlemagne, running through the European Quarter near key EU 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_69f76df28d8c819089f2c5799fe7d079 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f79467a8f481908d8fe3b582af2697 completed May 3, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a382cbcb1388190b89aa1e2e389ef36 completed June 21, 2026, 6:26 p.m.
NEDg Description generation batch_6a382d58e2b48190a1070bedf3aa5fff completed June 21, 2026, 6:28 p.m.
NED2 Entity disambiguation (via description) batch_6a382e1f37188190ac188d12cc6dce07 completed June 21, 2026, 6:31 p.m.
Created at: May 3, 2026, 4:03 p.m.