Triple

T3253490
Position Surface form Disambiguated ID Type / Status
Subject Senior Grand Warden E68239 entity
Predicate symbolicallyRepresents P129 FINISHED
Object strength 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: strength | Statement: [Senior Grand Warden, symbolicallyRepresents, strength]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: symbolicallyRepresents
Context triple: [Senior Grand Warden, symbolicallyRepresents, strength]
  • A. hasRepresentationIn
    Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
  • B. componentRepresents
    Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
  • C. symbolizes chosen
    Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
  • D. hasSymbolicForm
    Indicates that one entity serves as the symbolic representation or abstract form of another entity.
  • E. symbolicallyUses
    Indicates that one entity employs another as a symbol or representation to convey meaning, ideas, or associations rather than for its literal or practical function.
  • 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_69ad858f74408190bcbd07f967cd7bd0 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf640fd8819083c3c0cc41db2ffc completed March 8, 2026, 5:18 p.m.
PD Predicate disambiguation batch_69ada41ae74081909a0d1d696be8e35e completed March 8, 2026, 4:30 p.m.
Created at: March 8, 2026, 3:09 p.m.