Triple

T27750340
Position Surface form Disambiguated ID Type / Status
Subject Backgammon E702097 entity
Predicate hasScoringUnit P174682 FINISHED
Object points 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: points | Statement: [Backgammon, hasScoringUnit, points]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasScoringUnit
Context triple: [Backgammon, hasScoringUnit, points]
  • A. scoringUnit
    Indicates that one entity functions as a unit or component responsible for scoring or assigning scores to another entity.
  • B. hasScorecardUnit
    Indicates that one entity is associated with a specific scorecard unit used for measuring or evaluating its performance or outcomes.
  • C. hasScorer
    Indicates that one entity serves as the scorer (e.g., the one who scores points, goals, or evaluations) in relation to another entity.
  • D. hasScoreType
    Indicates that an entity is associated with a particular type or category of score.
  • E. hasScoreSystem
    Indicates that an entity uses, is governed by, or is associated with a particular scoring or rating system.
  • 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_69ef6a53c7388190899baa6daf42301c completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f6c5b7e46081909975b05f7298cc0e completed May 3, 2026, 3:49 a.m.
PD Predicate disambiguation batch_69f6c3f23ae081909a52801266063a3c completed May 3, 2026, 3:41 a.m.
PDg Predicate description generation batch_69f6c49069e48190a3486b6254a6645b completed May 3, 2026, 3:44 a.m.
Created at: April 27, 2026, 4:19 p.m.