Triple

T6592355
Position Surface form Disambiguated ID Type / Status
Subject Oslo commuter rail E148391 entity
Predicate connects P390 FINISHED
Object Jaren
Jaren is a village and transport hub in Gran municipality in Innlandet county, Norway, serving as a stop on the rail line north of Oslo.
E599685 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: Jaren | Statement: [Oslo commuter rail, connects, Jaren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jaren
Context triple: [Oslo commuter rail, connects, Jaren]
  • A. Jahren
    Jahren is a surname most notably associated with Hope Jahren, an American geochemist, geobiologist, and author known for her work on plant science and her memoir "Lab Girl."
  • B. Yillah
    Yillah is a mysterious, ethereal woman who serves as a symbolic and spiritual figure in Herman Melville’s novel "Mardi."
  • C. Jan
    Jan is a common Dutch given name, often used as a masculine form of "John" and borne by many notable figures in the Netherlands and other Dutch-speaking regions.
  • D. Jan
    Jan is an alternative romanization of the name Zhan, used to represent the same underlying name in different transliteration systems.
  • E. Jan
    Jan is a fictional character appearing in the Traveling Wilburys’ song “Tweeter and the Monkey Man,” which tells a noir-style crime story.
  • 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: Jaren
Triple: [Oslo commuter rail, connects, Jaren]
Generated description
Jaren is a village and transport hub in Gran municipality in Innlandet county, Norway, serving as a stop on the rail line north of Oslo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jaren
Target entity description: Jaren is a village and transport hub in Gran municipality in Innlandet county, Norway, serving as a stop on the rail line north of Oslo.
  • A. Jahren
    Jahren is a surname most notably associated with Hope Jahren, an American geochemist, geobiologist, and author known for her work on plant science and her memoir "Lab Girl."
  • B. Yillah
    Yillah is a mysterious, ethereal woman who serves as a symbolic and spiritual figure in Herman Melville’s novel "Mardi."
  • C. Jan
    Jan is a common Dutch given name, often used as a masculine form of "John" and borne by many notable figures in the Netherlands and other Dutch-speaking regions.
  • D. Jan
    Jan is the given name of the Dutch mathematician and philosopher Luitzen Egbertus Jan Brouwer, a founder of intuitionism in the foundations of mathematics.
  • E. Jan
    Jan is an alternative romanization of the name Zhan, used to represent the same underlying name in different transliteration systems.
  • 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_69c687e7b8688190811ffee72e096468 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aece1f848190a11676e072afb002 completed March 27, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbba656c81909c3876a8f2f7300e completed March 27, 2026, 6:26 p.m.
NEDg Description generation batch_69c6cd08a9c88190a481d4d3f8e680bf completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6cdc859cc8190bbae2efc39409021 completed March 27, 2026, 6:34 p.m.
Created at: March 27, 2026, 1:55 p.m.