Triple

T11776371
Position Surface form Disambiguated ID Type / Status
Subject Sándor Kocsis E280028 entity
Predicate goalsPerGameRatioForNationalTeam P71871 FINISHED
Object more than 1.0 LITERAL 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: more than 1.0 | Statement: [Sándor Kocsis, goalsPerGameRatioForNationalTeam, more than 1.0]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: goalsPerGameRatioForNationalTeam
Context triple: [Sándor Kocsis, goalsPerGameRatioForNationalTeam, more than 1.0]
  • A. internationalGoalsPerGameRatio chosen
    Indicates the ratio between the number of goals an entity scores in international matches and the number of international games it plays.
  • B. goalsForNationalTeam
    Indicates the number of goals an individual has scored while playing for their national team.
  • C. playedForNationalTeamFrom
    Indicates that an entity was a member of and played for a particular national team starting from a specified date or time period.
  • D. hasPlayedForNationalTeam
    Indicates that an athlete has been a member of and appeared in competition for a specified national team.
  • E. playedForNationalTeamUntil
    Indicates that an individual was a member of and actively played for a specified national team up to and including a particular end date or year.
  • F. None of above.

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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a8c2e8b08190a31b1e284fca2aee completed April 10, 2026, 7:37 a.m.
PD Predicate disambiguation batch_69d8a242cd8c819086ed6c5f292dc8cb completed April 10, 2026, 7:09 a.m.
Created at: April 8, 2026, 9:42 p.m.