Triple

T15360443
Position Surface form Disambiguated ID Type / Status
Subject Haram E367274 entity
Predicate containsSettlement P847 FINISHED
Object Vatne
Vatne is a village in Norway that forms part of the former municipality of Haram in Møre og Romsdal county.
E1160393 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: Vatne | Statement: [Haram, containsSettlement, Vatne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vatne
Context triple: [Haram, containsSettlement, Vatne]
  • A. Kvernes
    Kvernes is a village and historic parish area in Averøy Municipality in Møre og Romsdal county, Norway, known for its cultural heritage and scenic coastal landscape.
  • B. Vesle
    The Vesle is a river in northeastern France that flows through the Champagne region and was a significant geographic feature during World War I battles.
  • C. Flåvatn
    Flåvatn is a lake in Telemark, Norway, forming part of the Telemark Canal waterway system.
  • D. Nøklevann
    Nøklevann is a freshwater lake in the Østmarka forest area of Oslo, Norway, popular for outdoor recreation such as swimming, hiking, and fishing.
  • E. Sognsvann
    Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
  • 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: Vatne
Triple: [Haram, containsSettlement, Vatne]
Generated description
Vatne is a village in Norway that forms part of the former municipality of Haram in Møre og Romsdal county.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vatne
Target entity description: Vatne is a village in Norway that forms part of the former municipality of Haram in Møre og Romsdal county.
  • A. Kvernes
    Kvernes is a village and historic parish area in Averøy Municipality in Møre og Romsdal county, Norway, known for its cultural heritage and scenic coastal landscape.
  • B. Vesle
    The Vesle is a river in northeastern France that flows through the Champagne region and was a significant geographic feature during World War I battles.
  • C. Flåvatn
    Flåvatn is a lake in Telemark, Norway, forming part of the Telemark Canal waterway system.
  • D. Nøklevann
    Nøklevann is a freshwater lake in the Østmarka forest area of Oslo, Norway, popular for outdoor recreation such as swimming, hiking, and fishing.
  • E. Sognsvann
    Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4607408190ab281a7f7a8012d3 completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff364d82c48190b116528b5c00e918 completed May 9, 2026, 1:27 p.m.
NEDg Description generation batch_69ff37871dfc8190892d22ff66515c0b completed May 9, 2026, 1:32 p.m.
NED2 Entity disambiguation (via description) batch_69ff384962f88190964fc040a2a44aa8 completed May 9, 2026, 1:36 p.m.
Created at: April 10, 2026, 3:18 a.m.