Triple

T15030173
Position Surface form Disambiguated ID Type / Status
Subject T-bana E378321 entity
Predicate hasStation P35 FINISHED
Object T-Centralen E378318 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: T-Centralen | Statement: [T-bana, hasStation, T-Centralen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: T-Centralen
Context triple: [T-bana, hasStation, T-Centralen]
  • A. T-Centralen metro station chosen
    T-Centralen metro station is Stockholm’s central and busiest metro hub, known for its blue-themed art and for connecting all three of the city’s metro lines.
  • B. Sentrum station
    Sentrum station was the original name of what is now known as Stortinget metro station in central Oslo, Norway.
  • C. Copenhagen Central Station
    Copenhagen Central Station is the main railway hub of Copenhagen, Denmark, serving as a major national and international transit center for trains, buses, and local transport.
  • D. Schwedenplatz transport hub
    Schwedenplatz transport hub is a major public transportation interchange in central Vienna, connecting multiple metro, tram, and bus lines near the Danube Canal.
  • E. Stockholm City Station
    Stockholm City Station is a major underground railway station in central Stockholm that serves as a key interchange point for the city’s commuter rail network.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7e2416081908dfba48d7f7b4a84 completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69feb7db6f0081909ab35435c1e4ad13 completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 2:59 a.m.