Triple

T37927045
Position Surface form Disambiguated ID Type / Status
Subject Ebon E946120 entity
Predicate canAbsorb P30941 FINISHED
Object other beings into shadow dimension 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: other beings into shadow dimension | Statement: [Ebon, canAbsorb, other beings into shadow dimension]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: canAbsorb
Context triple: [Ebon, canAbsorb, other beings into shadow dimension]
  • A. canAbsorbFire
    Indicates the ability of one entity to take in, nullify, or withstand fire originating from another entity or source.
  • B. cannotBeDamagedBy
    Indicates that one entity is immune to harm, injury, or degradation caused by another specified entity or factor.
  • C. absorbed chosen
    Indicates that one entity takes in, soaks up, or assimilates another entity or substance.
  • D. affectedByWaterAbsorb
    Indicates that an entity’s state, behavior, or effectiveness is influenced or altered by another entity’s water-absorbing property or action.
  • E. affectedByVoltAbsorb
    Indicates that an entity is impacted by the Volt Absorb effect, typically converting incoming electric-based effects into a beneficial outcome rather than taking damage.
  • 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_69f76ef3b7248190892fb9706423be7c completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc7b78f9481909f4f8fc2e3fdcde1 completed May 6, 2026, 10:59 p.m.
PD Predicate disambiguation batch_69fbbd18c9908190928d274f8731dfa8 completed May 6, 2026, 10:13 p.m.
Created at: May 3, 2026, 4:20 p.m.