Triple

T1073468
Position Surface form Disambiguated ID Type / Status
Subject Bornholm E23381 entity
Predicate hasVillage P4011 FINISHED
Object Snogebæk
Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
E138842 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: Snogebæk | Statement: [Bornholm, hasVillage, Snogebæk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Snogebæk
Context triple: [Bornholm, hasVillage, Snogebæk]
  • A. Nordre Ål
    Nordre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • B. Femunden
    Femunden is one of Norway's largest lakes, located in the eastern part of the country near the Swedish border and known for its wilderness landscapes and outdoor recreation.
  • C. Hjørundfjord
    Hjørundfjord is a dramatic, narrow fjord in Norway’s Sunnmøre region, renowned for its steep mountain walls, deep waters, and scenic, relatively untouched natural landscapes.
  • D. Bergshamra
    Bergshamra is a residential district in the northern Stockholm urban area of Sweden, known for its proximity to green spaces and good public transport connections.
  • E. Søre Ål
    Søre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • 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: Snogebæk
Triple: [Bornholm, hasVillage, Snogebæk]
Generated description
Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Snogebæk
Target entity description: Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
  • A. Nordre Ål
    Nordre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • B. Femunden
    Femunden is one of Norway's largest lakes, located in the eastern part of the country near the Swedish border and known for its wilderness landscapes and outdoor recreation.
  • C. Hjørundfjord
    Hjørundfjord is a dramatic, narrow fjord in Norway’s Sunnmøre region, renowned for its steep mountain walls, deep waters, and scenic, relatively untouched natural landscapes.
  • D. Bergshamra
    Bergshamra is a residential district in the northern Stockholm urban area of Sweden, known for its proximity to green spaces and good public transport connections.
  • E. Søre Ål
    Søre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
  • 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_69a493ee1f908190992b5f0d1b04459b completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b92afad88190b7705923f71fc760 completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8303cbec8190a3b8a9bad2434ee7 completed March 7, 2026, 7:56 p.m.
NEDg Description generation batch_69ac83a2d15c8190abd20fa3a98b89cf completed March 7, 2026, 7:59 p.m.
NED2 Entity disambiguation (via description) batch_69ac84131858819097330fb693b3f0bd completed March 7, 2026, 8:01 p.m.
Created at: March 1, 2026, 7:42 p.m.