Triple

T22046113
Position Surface form Disambiguated ID Type / Status
Subject Colombina E544767 entity
Predicate maskUsage P145582 FINISHED
Object often unmasked or lightly masked 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: often unmasked or lightly masked | Statement: [Colombina, maskUsage, often unmasked or lightly masked]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: maskUsage
Context triple: [Colombina, maskUsage, often unmasked or lightly masked]
  • A. typicalMaskUsage chosen
    Indicates how a mask is most commonly or appropriately used in relation to an entity or situation.
  • B. usesMasking
    Indicates that one entity applies or employs a masking technique or mechanism in relation to another entity or process.
  • C. mask
    Indicates that one entity covers, conceals, or obscures another entity, typically to hide its identity, appearance, or specific features.
  • D. usesMaskIn
    Indicates that an entity wears or employs a mask while present in or interacting within a specified context or location.
  • E. mayMask
    Indicates that one entity is permitted or able to conceal, obscure, or hide another entity or its properties.
  • 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_69e11e32445c8190ab97089b48a130bb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1282f4a448190bca55348c457a4bd completed April 28, 2026, 9:35 p.m.
PD Predicate disambiguation batch_69e6f643ca74819083e8ab78e843f243 completed April 21, 2026, 4 a.m.
Created at: April 16, 2026, 8:26 p.m.