Triple

T32371449
Position Surface form Disambiguated ID Type / Status
Subject E313 motorway E827147 entity
Predicate hasServiceArea P82 FINISHED
Object Rotselaar service area
Rotselaar service area is a roadside rest and service facility located along Belgium’s E313 motorway, providing amenities for motorists such as fuel, parking, and basic traveler services.
 E2003759 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: Rotselaar service area | Statement: [E313 motorway, hasServiceArea, Rotselaar service area]
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: Rotselaar service area
Triple: [E313 motorway, hasServiceArea, Rotselaar service area]
Generated description
Rotselaar service area is a roadside rest and service facility located along Belgium’s E313 motorway, providing amenities for motorists such as fuel, parking, and basic traveler services.

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_69f349166d548190887b412fe908e2f4 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c12a4f948190b1c313045d622a6d completed May 3, 2026, 3:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a33e8b1c49c8190b094e4fca245a3b9 completed June 18, 2026, 12:46 p.m.
NEDg Description generation batch_6a33ea4c34688190b92a5cc87b56bd08 completed June 18, 2026, 12:53 p.m.
NED2 Entity disambiguation (via description) batch_6a342cb4168c8190bdbf08ddae3d6811 completed June 18, 2026, 5:36 p.m.
Created at: May 1, 2026, 12:50 a.m.