Triple

T3272101
Position Surface form Disambiguated ID Type / Status
Subject Hamar E68670 entity
Predicate hasRailwayStation P918 FINISHED
Object Hamar Station E331574 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: Hamar Station | Statement: [Hamar, hasRailwayStation, Hamar Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamar Station
Context triple: [Hamar, hasRailwayStation, Hamar Station]
  • A. Hamar Station chosen
    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.
  • B. Askim Station
    Askim Station is a railway station serving the town of Askim in Viken county, Norway, on the Eastern Østfold Line.
  • C. 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.
  • D. Datunlu East station
    Datunlu East station is a Beijing Subway interchange station in northern Beijing that serves as a key stop on Line 5 and connects to other lines in the city’s metro network.
  • E. Khimvolokno station
    Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adaff6308881908886a44804a0bb09 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28f0793e08190af55ee16e5091451 completed March 12, 2026, 10:01 a.m.
Created at: March 8, 2026, 3:10 p.m.