Triple

T594552
Position Surface form Disambiguated ID Type / Status
Subject Northern Norway E17350 entity
Predicate majorCity P316 FINISHED
Object Alta
Alta is a town in northern Norway known for its Arctic location, winter sports, and proximity to the Northern Lights.
 E78263 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: Alta | Statement: [Northern Norway, majorCity, Alta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alta
Context triple: [Northern Norway, majorCity, Alta]
  • A. Arrah
    Arrah is a historic town in the Indian state of Bihar, known for its role as a key site of conflict during the Indian Rebellion of 1857.
  • B. Madera
    Madera is a city in California’s San Joaquin Valley known primarily as the administrative and economic center of Madera County.
  • C. Sonora
    Sonora is a large northwestern Mexican state bordering the United States, known for its desert landscapes, cattle ranching, and significant industrial and agricultural production.
  • D. Sonora
    Sonora is a small historic city in California’s Sierra Nevada foothills known for its Gold Rush heritage and role as a regional hub for tourism and outdoor recreation.
  • E. Pinales
    Pinales is the botanical order of coniferous trees and shrubs that includes pines, firs, spruces, and related needle-leaved, cone-bearing plants.
  • 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: Alta
Triple: [Northern Norway, majorCity, Alta]
Generated description
Alta is a town in northern Norway known for its Arctic location, winter sports, and proximity to the Northern Lights.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alta
Target entity description: Alta is a town in northern Norway known for its Arctic location, winter sports, and proximity to the Northern Lights.
  • A. Arrah
    Arrah is a historic town in the Indian state of Bihar, known for its role as a key site of conflict during the Indian Rebellion of 1857.
  • B. Madera
    Madera is a city in California’s San Joaquin Valley known primarily as the administrative and economic center of Madera County.
  • C. Sonora
    Sonora is a large northwestern Mexican state bordering the United States, known for its desert landscapes, cattle ranching, and significant industrial and agricultural production.
  • D. Sonora
    Sonora is a small historic city in California’s Sierra Nevada foothills known for its Gold Rush heritage and role as a regional hub for tourism and outdoor recreation.
  • E. Pinales
    Pinales is the botanical order of coniferous trees and shrubs that includes pines, firs, spruces, and related needle-leaved, cone-bearing plants.
  • 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49bd15c5881909b59ed4c88687e7b completed March 1, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69a566fce9808190931b7c88b5c5686f completed March 2, 2026, 10:31 a.m.
NEDg Description generation batch_69a5678d8e1881908da2b274f6bac0b9 completed March 2, 2026, 10:33 a.m.
NED2 Entity disambiguation (via description) batch_69a56808933c81909611d0aa11126ec6 completed March 2, 2026, 10:35 a.m.
Created at: March 1, 2026, 7:33 p.m.