Triple

T22151029
Position Surface form Disambiguated ID Type / Status
Subject Kampen E547411 entity
Predicate locatedNear P294 FINISHED
Object Galgeberg
Galgeberg is a neighborhood in Oslo, Norway, known for its urban residential character and proximity to the historic Kampen area.
 E1522153 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: Galgeberg | Statement: [Kampen, locatedNear, Galgeberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Galgeberg
Context triple: [Kampen, locatedNear, Galgeberg]
  • A. Maughold
    Maughold is a coastal parish and village on the Isle of Man known for its rugged cliffs, scenic coastline, and historic church with ancient Celtic crosses.
  • B. Golgos
    Golgos is a minor figure in Greek mythology associated with the lineage and cult of Aphrodite, particularly linked to the ancient city of Golgi in Cyprus.
  • C. Bataille
    Bataille is a French surname most famously associated with Georges Bataille, the influential 20th-century writer and philosopher known for his work on eroticism, transgression, and the sacred.
  • D. Yangikent
    Yangikent was a medieval Central Asian city that served as the political and administrative center of the Oghuz Turks.
  • E. Alberoda
    Alberoda is a town in Germany’s Saxon Ore Mountains known historically for its role in the region’s mining industry.
  • 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: Galgeberg
Triple: [Kampen, locatedNear, Galgeberg]
Generated description
Galgeberg is a neighborhood in Oslo, Norway, known for its urban residential character and proximity to the historic Kampen area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Galgeberg
Target entity description: Galgeberg is a neighborhood in Oslo, Norway, known for its urban residential character and proximity to the historic Kampen area.
  • A. Maughold
    Maughold is a coastal parish and village on the Isle of Man known for its rugged cliffs, scenic coastline, and historic church with ancient Celtic crosses.
  • B. Golgos
    Golgos is a minor figure in Greek mythology associated with the lineage and cult of Aphrodite, particularly linked to the ancient city of Golgi in Cyprus.
  • C. Bataille
    Bataille is a French surname most famously associated with Georges Bataille, the influential 20th-century writer and philosopher known for his work on eroticism, transgression, and the sacred.
  • D. Yangikent
    Yangikent was a medieval Central Asian city that served as the political and administrative center of the Oghuz Turks.
  • E. Alberoda
    Alberoda is a town in Germany’s Saxon Ore Mountains known historically for its role in the region’s mining industry.
  • 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_69e11e3b52088190ad5df386d01eb2fb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129f37dac8190a7cecb12f4271515 completed April 28, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a9704f4988190b03783c006929ad7 completed May 18, 2026, 4:35 a.m.
NEDg Description generation batch_6a0a97e509a88190a7f316cf340d010a completed May 18, 2026, 4:39 a.m.
NED2 Entity disambiguation (via description) batch_6a0a987daa208190bab5b7adec1913e8 completed May 18, 2026, 4:41 a.m.
Created at: April 16, 2026, 8:33 p.m.