Triple

T7044360
Position Surface form Disambiguated ID Type / Status
Subject Ludvig Forssell E163593 entity
Predicate employer P7 FINISHED
Object Konami (former) E631089 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: Konami (former) | Statement: [Ludvig Forssell, employer, Konami (former)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konami (former)
Context triple: [Ludvig Forssell, employer, Konami (former)]
  • A. Konami chosen
    Konami is a major Japanese entertainment company best known for developing and publishing popular video game franchises such as Metal Gear, Castlevania, and Silent Hill.
  • B. Capcom
    Capcom is a Japanese video game developer and publisher best known for creating major franchises such as Resident Evil, Street Fighter, and Monster Hunter.
  • C. Midway Games
    Midway Games was an American video game company best known for publishing and developing popular arcade and console titles such as the Mortal Kombat series.
  • D. Sega
    Sega is a Japanese video game and entertainment company best known for its iconic consoles and franchises such as Sonic the Hedgehog.
  • E. Sony
    Sony is a Japanese multinational conglomerate best known for its consumer electronics, gaming (PlayStation), entertainment, and imaging products.
  • 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_69c6885f598c8190b6b6495c59d8d962 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e23730888190a827ca5c61c4eed0 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7887799f48190b4fa311defd8e9fd completed March 28, 2026, 7:51 a.m.
Created at: March 27, 2026, 2:37 p.m.