Triple

T3145347
Position Surface form Disambiguated ID Type / Status
Subject Hamar municipality E65749 entity
Predicate contains P35 FINISHED
Object Hamar Station
Hamar Station is a railway station in the town of Hamar in Innlandet county, Norway, serving as a regional transport hub on the country’s rail network.
 E331574 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: Hamar Station | Statement: [Hamar municipality, contains, Hamar Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hamar Station
Context triple: [Hamar municipality, contains, Hamar Station]
  • A. Askim Station
    Askim Station is a railway station serving the town of Askim in Viken county, Norway, on the Eastern Østfold Line.
  • B. Jubany Station
    Jubany Station is an Argentine Antarctic research base located on King George Island near the Antarctic Peninsula, supporting scientific studies in fields such as glaciology, biology, and atmospheric science.
  • C. Khimvolokno station
    Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • D. Bornova station
    Bornova station is a key terminal stop on the İzmir Metro system serving the Bornova district of İzmir, Turkey.
  • E. Luz Station
    Luz Station is a historic railway station and major transportation hub in São Paulo, Brazil, known for its distinctive architecture and cultural significance.
  • 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: Hamar Station
Triple: [Hamar municipality, contains, Hamar Station]
Generated description
Hamar Station is a railway station in the town of Hamar in Innlandet county, Norway, serving as a regional transport hub on the country’s rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hamar Station
Target entity description: Hamar Station is a railway station in the town of Hamar in Innlandet county, Norway, serving as a regional transport hub on the country’s rail network.
  • A. Askim Station
    Askim Station is a railway station serving the town of Askim in Viken county, Norway, on the Eastern Østfold Line.
  • B. Jubany Station
    Jubany Station is an Argentine Antarctic research base located on King George Island near the Antarctic Peninsula, supporting scientific studies in fields such as glaciology, biology, and atmospheric science.
  • C. Khimvolokno station
    Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • D. Bornova station
    Bornova station is a key terminal stop on the İzmir Metro system serving the Bornova district of İzmir, Turkey.
  • E. Luz Station
    Luz Station is a historic railway station and major transportation hub in São Paulo, Brazil, known for its distinctive architecture and cultural significance.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada59797788190a8d71262888c5df0 completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224f18e80819083be53c556d56947 completed March 12, 2026, 2:29 a.m.
NEDg Description generation batch_69b2271961048190906b6fa25e4b560c completed March 12, 2026, 2:38 a.m.
NED2 Entity disambiguation (via description) batch_69b227becba08190b5e4b3dae277ce51 completed March 12, 2026, 2:41 a.m.
Created at: March 8, 2026, 3:05 p.m.