Triple

T15216470
Position Surface form Disambiguated ID Type / Status
Subject Bybanen E363648 entity
Predicate terminus P388 FINISHED
Object Nesttun
Nesttun is a neighborhood and commercial center in the Fana borough of Bergen, Norway, serving as an important local transport hub.
E1143506 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: Nesttun | Statement: [Bybanen, terminus, Nesttun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nesttun
Context triple: [Bybanen, terminus, Nesttun]
  • A. Nannfeldt
    Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
  • B. Norén
    Norén is a Swedish surname, notably borne by actress Noomi Rapace before she adopted her stage name.
  • C. Nieste
    Nieste is a small settlement located within Germany's historic Westphalia region.
  • D. Nurn
    Nurn is a fertile, southern region of Mordor in J.R.R. Tolkien’s Middle-earth, known for its great inland sea and farmlands worked by slaves to provision Sauron’s armies.
  • E. Neltume
    Neltume is a small town in southern Chile known for its proximity to lakes, forests, and ecotourism activities in the Andes.
  • 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: Nesttun
Triple: [Bybanen, terminus, Nesttun]
Generated description
Nesttun is a neighborhood and commercial center in the Fana borough of Bergen, Norway, serving as an important local transport hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nesttun
Target entity description: Nesttun is a neighborhood and commercial center in the Fana borough of Bergen, Norway, serving as an important local transport hub.
  • A. Nannfeldt
    Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
  • B. Norén
    Norén is a Swedish surname, notably borne by actress Noomi Rapace before she adopted her stage name.
  • C. Nieste
    Nieste is a small settlement located within Germany's historic Westphalia region.
  • D. Nurn
    Nurn is a fertile, southern region of Mordor in J.R.R. Tolkien’s Middle-earth, known for its great inland sea and farmlands worked by slaves to provision Sauron’s armies.
  • E. Neltume
    Neltume is a small town in southern Chile known for its proximity to lakes, forests, and ecotourism activities in the Andes.
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed343f51481908f04c35d37b39ad2 completed May 9, 2026, 6:25 a.m.
NEDg Description generation batch_69fed44b2e3c8190aad111e2bc2b56a2 completed May 9, 2026, 6:29 a.m.
NED2 Entity disambiguation (via description) batch_69fed547192c8190b89755fff48ca620 completed May 9, 2026, 6:33 a.m.
Created at: April 10, 2026, 3:11 a.m.