Triple

T8172239
Position Surface form Disambiguated ID Type / Status
Subject Tjøme E190849 entity
Predicate hasIsland P970 FINISHED
Object Hvasser
Hvasser is a coastal island in Vestfold og Telemark, Norway, known for its fishing villages, beaches, and role as a popular summer holiday destination.
E716114 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: Hvasser | Statement: [Tjøme, hasIsland, Hvasser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hvasser
Context triple: [Tjøme, hasIsland, Hvasser]
  • A. Vedder
    Vedder is a surname most notably associated with Elihu Vedder, an American symbolist painter, book illustrator, and muralist active in the late 19th and early 20th centuries.
  • B. Veddesta
    Veddesta is an industrial and commercial area in Järfälla Municipality, northwest of central Stockholm, Sweden.
  • C. Eemnes
    Eemnes is a small town and municipality in the central Netherlands known for its characteristic polder landscape and historic village centers.
  • D. Hadsel
    Hadsel is a coastal municipality in Nordland county, Norway, known for encompassing several islands in the Vesterålen archipelago, including parts of Hadseløya, Langøya, and Austvågøya.
  • E. Tejn
    Tejn is a small coastal town and fishing port on the Danish island of Bornholm in the Baltic Sea.
  • 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: Hvasser
Triple: [Tjøme, hasIsland, Hvasser]
Generated description
Hvasser is a coastal island in Vestfold og Telemark, Norway, known for its fishing villages, beaches, and role as a popular summer holiday destination.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hvasser
Target entity description: Hvasser is a coastal island in Vestfold og Telemark, Norway, known for its fishing villages, beaches, and role as a popular summer holiday destination.
  • A. Vedder
    Vedder is a surname most notably associated with Elihu Vedder, an American symbolist painter, book illustrator, and muralist active in the late 19th and early 20th centuries.
  • B. Veddesta
    Veddesta is an industrial and commercial area in Järfälla Municipality, northwest of central Stockholm, Sweden.
  • C. Eemnes
    Eemnes is a small town and municipality in the central Netherlands known for its characteristic polder landscape and historic village centers.
  • D. Hadsel
    Hadsel is a coastal municipality in Nordland county, Norway, known for encompassing several islands in the Vesterålen archipelago, including parts of Hadseløya, Langøya, and Austvågøya.
  • E. Tejn
    Tejn is a small coastal town and fishing port on the Danish island of Bornholm in the Baltic Sea.
  • 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_69ca82c1c0a08190bf8692b4d91a03ca completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4807c9808190ad91a9c688a4c7fd completed March 31, 2026, 4:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbf65ed508190abb60f9189f43e5c completed April 1, 2026, 6:47 a.m.
NEDg Description generation batch_69ccc312a8608190b899394752ef375f completed April 1, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69ccd84893488190ae5376524650d5c4 completed April 1, 2026, 8:33 a.m.
Created at: March 30, 2026, 5:39 p.m.