Triple

T1356090
Position Surface form Disambiguated ID Type / Status
Subject Port of Oslo E28991 entity
Predicate operator P179 FINISHED
Object Oslo Havn KF
Oslo Havn KF is the municipal enterprise responsible for managing and developing the Port of Oslo’s harbor infrastructure and maritime operations.
 E156720 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: Oslo Havn KF | Statement: [Port of Oslo, operator, Oslo Havn KF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oslo Havn KF
Context triple: [Port of Oslo, operator, Oslo Havn KF]
  • A. Vålerenga
    Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
  • B. Stabæk Fotball
    Stabæk Fotball is a Norwegian professional football club based in Bærum, known for competing in the country’s top divisions and developing notable players and coaches.
  • C. Lillehammer FK
    Lillehammer FK is a Norwegian football club based in the town of Lillehammer, competing in the lower tiers of the national league system.
  • D. Kvik Halden FK
    Kvik Halden FK is a Norwegian football club based in the town of Halden, known for competing in the national league system.
  • E. Örgryte IS
    Örgryte IS is a Swedish sports club best known for its historic football team, one of the oldest in Sweden, based in Gothenburg.
  • 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: Oslo Havn KF
Triple: [Port of Oslo, operator, Oslo Havn KF]
Generated description
Oslo Havn KF is the municipal enterprise responsible for managing and developing the Port of Oslo’s harbor infrastructure and maritime operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oslo Havn KF
Target entity description: Oslo Havn KF is the municipal enterprise responsible for managing and developing the Port of Oslo’s harbor infrastructure and maritime operations.
  • A. Vålerenga
    Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
  • B. Stabæk Fotball
    Stabæk Fotball is a Norwegian professional football club based in Bærum, known for competing in the country’s top divisions and developing notable players and coaches.
  • C. Lillehammer FK
    Lillehammer FK is a Norwegian football club based in the town of Lillehammer, competing in the lower tiers of the national league system.
  • D. Kvik Halden FK
    Kvik Halden FK is a Norwegian football club based in the town of Halden, known for competing in the national league system.
  • E. Örgryte IS
    Örgryte IS is a Swedish sports club best known for its historic football team, one of the oldest in Sweden, based in Gothenburg.
  • 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_69a498571d248190a0ac9eb02d97097f completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c28c8dd0819082f94c9e7c837c5f completed March 1, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce6e264481909f7cb907486d3e08 completed March 8, 2026, 1:18 a.m.
NEDg Description generation batch_69accf141c3481909ae5ea849aee7604 completed March 8, 2026, 1:21 a.m.
NED2 Entity disambiguation (via description) batch_69accfb8acfc8190bba379d8bb114c29 completed March 8, 2026, 1:24 a.m.
Created at: March 1, 2026, 7:56 p.m.