Triple

T35287174
Position Surface form Disambiguated ID Type / Status
Subject Ryfylke Tunnel E1019116 entity
Predicate NorwegianName P24009 FINISHED
Object Ryfylketunnelen
Ryfylketunnelen is a subsea road tunnel in southwestern Norway that connects Stavanger to the Ryfylke region and is among the longest and deepest undersea road tunnels in the world.
E2134816 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: Ryfylketunnelen | Statement: [Ryfylke Tunnel, NorwegianName, Ryfylketunnelen]
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: Ryfylketunnelen
Triple: [Ryfylke Tunnel, NorwegianName, Ryfylketunnelen]
Generated description
Ryfylketunnelen is a subsea road tunnel in southwestern Norway that connects Stavanger to the Ryfylke region and is among the longest and deepest undersea road tunnels in the world.

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_69f76de6d39c8190bb11342e4b91ff2b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78fe35fd88190b2154c89e1b7ffd8 completed May 3, 2026, 6:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3819dd37008190968d967d8740ffbb completed June 21, 2026, 5:05 p.m.
NEDg Description generation batch_6a381a89da088190b3b7e52b0531b692 completed June 21, 2026, 5:08 p.m.
NED2 Entity disambiguation (via description) batch_6a381b3c8ecc8190a22b608d4cb29b2a completed June 21, 2026, 5:11 p.m.
Created at: May 3, 2026, 4:03 p.m.