Triple

T28944796
Position Surface form Disambiguated ID Type / Status
Subject N5 national route E730549 entity
Predicate hasJunctionWith P1018 FINISHED
Object R74 regional route
The R74 is a South African regional road that connects towns in KwaZulu-Natal and the Free State, serving as an important link between the Drakensberg region and major national routes.
E1849811 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: R74 regional route | Statement: [N5 national route, hasJunctionWith, R74 regional route]
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: R74 regional route
Triple: [N5 national route, hasJunctionWith, R74 regional route]
Generated description
The R74 is a South African regional road that connects towns in KwaZulu-Natal and the Free State, serving as an important link between the Drakensberg region and major national routes.

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_69f043ea0aa88190a25acbf46157995a completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f65b86495081909fb46fa7656f5059 completed May 2, 2026, 8:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2537948a048190bea36139fd81145b completed June 7, 2026, 9:19 a.m.
NEDg Description generation batch_6a253b9227ec8190b3887b13af5938b3 completed June 7, 2026, 9:36 a.m.
NED2 Entity disambiguation (via description) batch_6a253fa2b67c8190a8ff6e0a1d129cd7 completed June 7, 2026, 9:53 a.m.
Created at: April 28, 2026, 8:39 a.m.