Triple

T27453611
Position Surface form Disambiguated ID Type / Status
Subject A15 motorway E692518 entity
Predicate hasJunctionWith P1018 FINISHED
Object A8 motorway
The A8 motorway is a major European highway that serves as a key east–west transport corridor, connecting important cities and linking with several other primary motorways.
 E2284244 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: A8 motorway | Statement: [A15 motorway, hasJunctionWith, A8 motorway]
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: A8 motorway
Triple: [A15 motorway, hasJunctionWith, A8 motorway]
Generated description
The A8 motorway is a major European highway that serves as a key east–west transport corridor, connecting important cities and linking with several other primary motorways.

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_69ef5207903881909427745cda05d27a completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62dc7c830819092e3f52733c8f60e completed May 2, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7c040ed1bc8190b599765f9ab982bc completed Aug. 12, 2026, 5:26 a.m.
NEDg Description generation batch_6a7c045c8bd4819087266a8a3478722b completed Aug. 12, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_6a7c04800e308190857a6c41b70766bb completed Aug. 12, 2026, 5:28 a.m.
Created at: April 27, 2026, 12:48 p.m.