Triple

T13808081
Position Surface form Disambiguated ID Type / Status
Subject Toten E331810 entity
Predicate hasSettlement P1068 FINISHED
Object Kapp
Kapp is a small village in Innlandet county, Norway, situated on the shores of Lake Mjøsa and known historically for its dairy industry.
E1062765 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: Kapp | Statement: [Toten, hasSettlement, Kapp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kapp
Context triple: [Toten, hasSettlement, Kapp]
  • A. Kapp
    Kapp is a surname most notably associated with Joe Kapp, a former professional football quarterback and coach.
  • B. Kapaa
    Kapaa is a coastal town on the east side of Kauai, Hawaii, known for its beaches, resorts, and small-town atmosphere.
  • C. Kapp Weyprecht
    Kapp Weyprecht is a remote Arctic headland on Kvitøya in the Svalbard archipelago, named after the Austro-Hungarian polar explorer Karl Weyprecht.
  • D. Koubia
    Koubia is a town in the Middle Guinea region of Guinea that serves as an important local administrative and commercial center.
  • E. Kaa
    Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
  • 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: Kapp
Triple: [Toten, hasSettlement, Kapp]
Generated description
Kapp is a small village in Innlandet county, Norway, situated on the shores of Lake Mjøsa and known historically for its dairy industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kapp
Target entity description: Kapp is a small village in Innlandet county, Norway, situated on the shores of Lake Mjøsa and known historically for its dairy industry.
  • A. Kapp
    Kapp is a surname most notably associated with Joe Kapp, a former professional football quarterback and coach.
  • B. Kapaa
    Kapaa is a coastal town on the east side of Kauai, Hawaii, known for its beaches, resorts, and small-town atmosphere.
  • C. Kapp Weyprecht
    Kapp Weyprecht is a remote Arctic headland on Kvitøya in the Svalbard archipelago, named after the Austro-Hungarian polar explorer Karl Weyprecht.
  • D. Koubia
    Koubia is a town in the Middle Guinea region of Guinea that serves as an important local administrative and commercial center.
  • E. Kaa
    Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026eae8481908b8880635e6a9152 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b08fbc348190a199c5d92e0e46be completed May 3, 2026, 8:31 p.m.
NEDg Description generation batch_69f7b15143108190a49a09afba93eb45 completed May 3, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_69f7b50c31ac81909b17013d57dda164 completed May 3, 2026, 8:50 p.m.
Created at: April 9, 2026, 10:12 p.m.