Triple

T21024662
Position Surface form Disambiguated ID Type / Status
Subject Handen station E517907 entity
Predicate line P1293 FINISHED
Object Nynäsbanan
Nynäsbanan is a Swedish railway line in the Stockholm region that connects the city with its southeastern suburbs and coastal areas.
E1464196 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: Nynäsbanan | Statement: [Handen station, line, Nynäsbanan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nynäsbanan
Context triple: [Handen station, line, Nynäsbanan]
  • A. Bannans
    Bannans is a small commune in the Doubs department of eastern France, situated in the Bourgogne-Franche-Comté region.
  • B. Banana North
    Banana North is a rural locality within Queensland’s Banana Shire, known primarily for its agricultural landscape and small population.
  • C. Banna
    Banna is the Latin name of Birdoswald Roman Fort, a key military site along Hadrian’s Wall in Roman Britain.
  • D. Banna
    Banna is an Omotic language spoken by the Banna people of southwestern Ethiopia, closely related to other languages of the region.
  • E. Nanas
    Nanas are a series of colorful, voluptuous female sculptures by Niki de Saint Phalle that celebrate femininity, joy, and empowerment.
  • 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: Nynäsbanan
Triple: [Handen station, line, Nynäsbanan]
Generated description
Nynäsbanan is a Swedish railway line in the Stockholm region that connects the city with its southeastern suburbs and coastal areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nynäsbanan
Target entity description: Nynäsbanan is a Swedish railway line in the Stockholm region that connects the city with its southeastern suburbs and coastal areas.
  • A. Bannans
    Bannans is a small commune in the Doubs department of eastern France, situated in the Bourgogne-Franche-Comté region.
  • B. Banana North
    Banana North is a rural locality within Queensland’s Banana Shire, known primarily for its agricultural landscape and small population.
  • C. Banna
    Banna is an Omotic language spoken by the Banna people of southwestern Ethiopia, closely related to other languages of the region.
  • D. Banna
    Banna is the Latin name of Birdoswald Roman Fort, a key military site along Hadrian’s Wall in Roman Britain.
  • E. Nanas
    Nanas are a series of colorful, voluptuous female sculptures by Niki de Saint Phalle that celebrate femininity, joy, and empowerment.
  • 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_69e0b50262b081909bc488937145eb73 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc6059908190bf5c9ef9c30f1a32 completed April 21, 2026, 4:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09474123ac8190b335000f96df7473 completed May 17, 2026, 4:42 a.m.
NEDg Description generation batch_6a09490822ac81909966eb2013ddb837 completed May 17, 2026, 4:50 a.m.
NED2 Entity disambiguation (via description) batch_6a094a078eb08190857d156dcadf35fc completed May 17, 2026, 4:54 a.m.
Created at: April 16, 2026, 1:55 p.m.