Triple

T37578601
Position Surface form Disambiguated ID Type / Status
Subject Vampire Queen E934891 entity
Predicate canConsume P188302 FINISHED
Object shades of red instead of blood 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: shades of red instead of blood | Statement: [Vampire Queen, canConsume, shades of red instead of blood]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: canConsume
Context triple: [Vampire Queen, canConsume, shades of red instead of blood]
  • A. canUse
    Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
  • B. canConvey
    Indicates that one entity is capable of transmitting, expressing, or carrying another (such as information, meaning, or an object) from a source to a target.
  • C. isConsumedIn
    Indicates that one entity is used up, ingested, or otherwise expended as part of a process, event, or action involving another entity.
  • D. canHold
    Indicates that one entity has the capacity or ability to contain, support, or carry another entity.
  • E. canHandle
    Indicates that an entity has the ability or capacity to manage, process, or deal with another entity or situation.
  • 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_69f76ecd99148190be327e391a70f5b6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba61dff5081909fec88a7aeb0c8a1 completed May 6, 2026, 8:35 p.m.
PD Predicate disambiguation batch_69fba350e9a8819095893229d9643572 completed May 6, 2026, 8:23 p.m.
PDg Predicate description generation batch_69fba61d2214819091ae6793bfefb1f0 completed May 6, 2026, 8:35 p.m.
Created at: May 3, 2026, 4:17 p.m.