Triple

T17087415
Position Surface form Disambiguated ID Type / Status
Subject Osterøy Municipality E414633 entity
Predicate hasSettlement P1068 FINISHED
Object Tysse
Tysse is a small village in Osterøy Municipality in Vestland county, Norway, known for its scenic fjord-side setting and rural character.
 E1249120 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: Tysse | Statement: [Osterøy Municipality, hasSettlement, Tysse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tysse
Context triple: [Osterøy Municipality, hasSettlement, Tysse]
  • A. Tysso
    Tysso is a river in the municipality of Ulvik in western Norway, known for flowing through a scenic fjord landscape.
  • B. Tyge
    Tyge is the original Danish given name of the renowned 16th-century astronomer Tycho Brahe.
  • C. Tlass
    Tlass is a Syrian family name most prominently associated with Mustafa Tlass, a long-serving defense minister under Hafez al-Assad.
  • D. Minn-Erva
    Minn-Erva is a Kree sniper and Starforce member in the Marvel Cinematic Universe, appearing as an antagonist in the film "Captain Marvel."
  • E. Tyros
    Tyros is a coastal town in the traditional Tsakonian region of the eastern Peloponnese in Greece, known for its beaches and local maritime heritage.
  • 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: Tysse
Triple: [Osterøy Municipality, hasSettlement, Tysse]
Generated description
Tysse is a small village in Osterøy Municipality in Vestland county, Norway, known for its scenic fjord-side setting and rural character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tysse
Target entity description: Tysse is a small village in Osterøy Municipality in Vestland county, Norway, known for its scenic fjord-side setting and rural character.
  • A. Tysso
    Tysso is a river in the municipality of Ulvik in western Norway, known for flowing through a scenic fjord landscape.
  • B. Tyge
    Tyge is the original Danish given name of the renowned 16th-century astronomer Tycho Brahe.
  • C. Tlass
    Tlass is a Syrian family name most prominently associated with Mustafa Tlass, a long-serving defense minister under Hafez al-Assad.
  • D. Minn-Erva
    Minn-Erva is a Kree sniper and Starforce member in the Marvel Cinematic Universe, appearing as an antagonist in the film "Captain Marvel."
  • E. Tyros
    Tyros is a coastal town in the traditional Tsakonian region of the eastern Peloponnese in Greece, known for its beaches and local maritime heritage.
  • 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_69d886cef44c8190ba56c44b4e863e64 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbe7ccb48190b8fb39e2a0ba0782 completed April 18, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012ee81fd08190a7e1f5958fbe3b97 completed May 11, 2026, 1:20 a.m.
NEDg Description generation batch_6a012ff7788c819086b2e6c0e382014c completed May 11, 2026, 1:25 a.m.
NED2 Entity disambiguation (via description) batch_6a0130dbe1f8819095b2d36882bf3287 completed May 11, 2026, 1:29 a.m.
Created at: April 10, 2026, 5:35 a.m.