Triple

T5290853
Position Surface form Disambiguated ID Type / Status
Subject Flytoget E119736 entity
Predicate stationServed P6301 FINISHED
Object Oslo S E150936 NE FINISHED

How this triple was built (2 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 S | Statement: [Flytoget, stationServed, Oslo S]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo S
Context triple: [Flytoget, stationServed, Oslo S]
  • A. Osedalen
    Osedalen is a village in Froland municipality in Agder county in southern Norway.
  • B. MUNCH, Oslo
    MUNCH, Oslo is a major contemporary art museum in Norway dedicated primarily to the life and works of Edvard Munch, housed in a striking waterfront building that has become a landmark of Oslo’s skyline.
  • C. Sarpsborg
    Sarpsborg is a historic city and municipality in Viken county, Norway, known as one of the country’s oldest towns and an important industrial and administrative center in the Østfold region.
  • D. OsloMet
    OsloMet is a public university in Oslo, Norway, known for its professionally oriented programs and research in fields such as social sciences, health, technology, and education.
  • E. Sentrum, Oslo chosen
    Sentrum is the central borough of Oslo, Norway, encompassing the city’s main downtown area, key commercial districts, and major transport hubs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84eac7b88190900142bd1310c0fd completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf10dfc2948190b65f5e4c9388a5cb completed March 21, 2026, 9:42 p.m.
Created at: March 20, 2026, 1:52 p.m.