Triple

T30197111
Position Surface form Disambiguated ID Type / Status
Subject European route E74 E767662 entity
Predicate hasJunctionWith P1018 FINISHED
Object European route E717
European route E717 is a short European B-class road in Italy that connects the city of Turin with the A6 motorway toward Savona, linking inland northern Italy to the Ligurian coast.
E1914164 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: European route E717 | Statement: [European route E74, hasJunctionWith, European route E717]
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: European route E717
Triple: [European route E74, hasJunctionWith, European route E717]
Generated description
European route E717 is a short European B-class road in Italy that connects the city of Turin with the A6 motorway toward Savona, linking inland northern Italy to the Ligurian coast.

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_69f2247db1108190835c0727c97637c3 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67fc237608190b6542b56038a7fe4 completed May 2, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a279897d1d48190812d97ff355491ed completed June 9, 2026, 4:37 a.m.
NEDg Description generation batch_6a27995cdae081908306889d8242ee90 completed June 9, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_6a2799ce12748190802bc7d7e5b71b33 completed June 9, 2026, 4:42 a.m.
Created at: April 29, 2026, 7:30 p.m.