Triple

T20018372
Position Surface form Disambiguated ID Type / Status
Subject Herøy (Møre og Romsdal) E494781 entity
Predicate locatedNear P294 FINISHED
Object Stadhavet
Stadhavet is a notoriously rough stretch of open sea off the western coast of Norway, known for its challenging weather and hazardous sailing conditions.
 E1407193 NE FINISHED

How this triple was built (4 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: Stadhavet | Statement: [Herøy (Møre og Romsdal), locatedNear, Stadhavet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stadhavet
Context triple: [Herøy (Møre og Romsdal), locatedNear, Stadhavet]
  • A. Stolica
    Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
  • B. Šolta
    Šolta is a small Croatian island in the Adriatic Sea, known for its tranquil villages, olive groves, and clear bays, located just off the coast from the city of Split.
  • C. Unstad
    Unstad is a small coastal village in Norway’s Lofoten archipelago, renowned for its dramatic Arctic scenery and world-class cold-water surfing.
  • D. Waase
    Waase is a small village on the island of Ummanz in the German state of Mecklenburg-Vorpommern.
  • E. Schwedenkai
    Schwedenkai is a passenger and cargo ferry terminal in the Port of Kiel, Germany, primarily serving routes to and from Sweden.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Stadhavet
Triple: [Herøy (Møre og Romsdal), locatedNear, Stadhavet]
Generated description
Stadhavet is a notoriously rough stretch of open sea off the western coast of Norway, known for its challenging weather and hazardous sailing conditions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stadhavet
Target entity description: Stadhavet is a notoriously rough stretch of open sea off the western coast of Norway, known for its challenging weather and hazardous sailing conditions.
  • A. Stolica
    Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
  • B. Šolta
    Šolta is a small Croatian island in the Adriatic Sea, known for its tranquil villages, olive groves, and clear bays, located just off the coast from the city of Split.
  • C. Unstad
    Unstad is a small coastal village in Norway’s Lofoten archipelago, renowned for its dramatic Arctic scenery and world-class cold-water surfing.
  • D. Waase
    Waase is a small village on the island of Ummanz in the German state of Mecklenburg-Vorpommern.
  • E. Schwedenkai
    Schwedenkai is a passenger and cargo ferry terminal in the Port of Kiel, Germany, primarily serving routes to and from Sweden.
  • F. None of above. chosen

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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6623e40748190b1abb0ead9acab4e completed April 20, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a080e286230819097e564d028e73ab5 completed May 16, 2026, 6:26 a.m.
NEDg Description generation batch_6a080ef87f08819091b4a76009b1c4ba completed May 16, 2026, 6:30 a.m.
NED2 Entity disambiguation (via description) batch_6a080f8bb81c819098d39ad6e1642aa8 completed May 16, 2026, 6:32 a.m.
Created at: April 11, 2026, 3:34 p.m.