Triple

T16914248
Position Surface form Disambiguated ID Type / Status
Subject Helsinki Olympic Stadium E410280 entity
Predicate architect P184 FINISHED
Object Toivo Jäntti E410280 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: Toivo Jäntti | Statement: [Helsinki Olympic Stadium, architect, Toivo Jäntti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toivo Jäntti
Context triple: [Helsinki Olympic Stadium, architect, Toivo Jäntti]
  • A. Toivo Jäntti chosen
    Toivo Jäntti was a Finnish architect best known for co-designing Helsinki’s Olympic Stadium, a landmark of modernist sports architecture.
  • B. Antti Järvenpää
    Antti Järvenpää is a Finnish public administrator who serves as the municipal manager of the municipality of Ruovesi.
  • C. Hannu Toivonen
    Hannu Toivonen is a Finnish computer scientist known for his contributions to data mining, pattern discovery, and artificial intelligence research.
  • D. Wiljo Tuompo
    Wiljo Tuompo was a Finnish military officer best known for his leadership role during the Winter War, particularly in the defense against Soviet forces.
  • E. Jukka Jalonen
    Jukka Jalonen is a highly successful Finnish ice hockey coach best known for leading Finland’s national team to multiple World Championship and Olympic medals.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3ca3f1a2c8190a512ccc09a080eb4 completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7be679c8190b9d0b0b9cfe185d3 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:30 a.m.