Triple

T10375734
Position Surface form Disambiguated ID Type / Status
Subject Jura-Nord vaudois E244500 entity
Predicate contains P35 FINISHED
Object Dizy
Dizy is a small municipality in the canton of Vaud in western Switzerland.
E860330 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: Dizy | Statement: [Jura-Nord vaudois, contains, Dizy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dizy
Context triple: [Jura-Nord vaudois, contains, Dizy]
  • A. Dwikozy
    Dwikozy is a village in southeastern Poland that serves as the seat of the local administrative district (gmina) within Sandomierz County.
  • B. Zog
    Zog is a children's picture book by Julia Donaldson, illustrated by Axel Scheffler, about an eager young dragon learning at dragon school.
  • C. Dinazad
    Dinazad is an alternate spelling of Dinarzad, the younger sister of Scheherazade in the classic Middle Eastern collection of tales known as One Thousand and One Nights.
  • D. Daisi
    Daisi is a Georgian opera by composer Zakharia Paliashvili, renowned as one of the classics of Georgian national opera repertoire.
  • E. Doozer
    Doozer is a television production company founded by Bill Lawrence, best known for producing series such as Scrubs, Cougar Town, and Ted Lasso.
  • 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: Dizy
Triple: [Jura-Nord vaudois, contains, Dizy]
Generated description
Dizy is a small municipality in the canton of Vaud in western Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dizy
Target entity description: Dizy is a small municipality in the canton of Vaud in western Switzerland.
  • A. Dwikozy
    Dwikozy is a village in southeastern Poland that serves as the seat of the local administrative district (gmina) within Sandomierz County.
  • B. Zog
    Zog is a children's picture book by Julia Donaldson, illustrated by Axel Scheffler, about an eager young dragon learning at dragon school.
  • C. Dinazad
    Dinazad is an alternate spelling of Dinarzad, the younger sister of Scheherazade in the classic Middle Eastern collection of tales known as One Thousand and One Nights.
  • D. Daisi
    Daisi is a Georgian opera by composer Zakharia Paliashvili, renowned as one of the classics of Georgian national opera repertoire.
  • E. Doozer
    Doozer is a television production company founded by Bill Lawrence, best known for producing series such as Scrubs, Cougar Town, and Ted Lasso.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e98106d081909d28e30d2fff6902 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d795754570819093747f80e32fffce completed April 9, 2026, 12:03 p.m.
NEDg Description generation batch_69d7bde050ac8190b87a0c81700ad1b1 completed April 9, 2026, 2:55 p.m.
NED2 Entity disambiguation (via description) batch_69d7e60afaf481909a0790c94e323143 completed April 9, 2026, 5:46 p.m.
Created at: April 6, 2026, 12:02 p.m.