Triple

T27181552
Position Surface form Disambiguated ID Type / Status
Subject Lene Christensen E683204 entity
Predicate typeOfGoalkeeper P34552 FINISHED
Object women's association football goalkeeper 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: women's association football goalkeeper | Statement: [Lene Christensen, typeOfGoalkeeper, women's association football goalkeeper]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfGoalkeeper
Context triple: [Lene Christensen, typeOfGoalkeeper, women's association football goalkeeper]
  • A. goalkeeperPositionRequirement
    Indicates the required or expected positioning of a goalkeeper relative to the play, goal, or field in a given situation.
  • B. goaltender chosen
    Indicates a relationship where an entity serves as the goalkeeper or primary defender of the goal for a team in a game or sport.
  • C. goalkeeperAction
    Indicates actions performed by a goalkeeper in the context of defending the goal, such as saving, catching, blocking, or distributing the ball.
  • D. backupGoalkeeper
    Indicates that one entity serves as the secondary or reserve goalkeeper for another team or primary goalkeeper.
  • E. goalkeeperInFinal
    Indicates that an entity served as a goalkeeper in the final match of a competition.
  • 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_69eefad086808190ab89816c0c300476 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69fda5003cdc8190a558501271389912 completed May 8, 2026, 8:55 a.m.
PD Predicate disambiguation batch_69fda05bfc2c819096821a5300e9bb24 completed May 8, 2026, 8:35 a.m.
Created at: April 27, 2026, 9:28 a.m.