Triple

T28322787
Position Surface form Disambiguated ID Type / Status
Subject Ferran Torres E717322 entity
Predicate scoredHatTrickAgainst P164268 FINISHED
Object Germany national football team NE NERFINISHED

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: Germany national football team | Statement: [Ferran Torres, scoredHatTrickAgainst, Germany national football team]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: scoredHatTrickAgainst
Context triple: [Ferran Torres, scoredHatTrickAgainst, Germany national football team]
  • A. scoredHatTrickAt
    Indicates that an entity (typically a player) scored three goals in a single game or match that took place at the specified location or event.
  • B. scoredFor
    Indicates that one entity achieved points or a score on behalf of another entity, such as a player scoring for a team.
  • C. premierLeagueHatTricks
    Indicates that the subject has scored one or more hat-tricks (three goals in a single match) in English Premier League games.
  • D. famousGoalAgainst
    Indicates that one entity is widely recognized for scoring a notable or iconic goal against another entity.
  • E. hasScoredFor
    Indicates that one entity has scored points, goals, or similar achievements on behalf of another entity, such as a team, organization, or side.
  • F. None of above. chosen

Provenance (4 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_69eff6e6c3b08190ad78de6ba7f04548 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f6492c10d08190a8dbfdb678697af2 completed May 2, 2026, 6:57 p.m.
PD Predicate disambiguation batch_69f641e0fde08190bf06a1c5b388aa84 completed May 2, 2026, 6:26 p.m.
PDg Predicate description generation batch_69f6430975b481909191219ad13ef77e completed May 2, 2026, 6:31 p.m.
Created at: April 28, 2026, 12:25 a.m.