Triple

T25703018
Position Surface form Disambiguated ID Type / Status
Subject Fantomina E644513 entity
Predicate featuresCharacterDisguisesAs P93957 FINISHED
Object prostitute 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: prostitute | Statement: [Fantomina, featuresCharacterDisguisesAs, prostitute]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuresCharacterDisguisesAs
Context triple: [Fantomina, featuresCharacterDisguisesAs, prostitute]
  • A. hostsCharacterInDisguise
    Indicates that a host entity accommodates or presents a character who is concealed under a false identity or disguise.
  • B. featuresCharacterWith chosen
    Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
  • C. disguisedAs
    Indicates that one entity is intentionally presenting itself as, or made to appear as, another entity in order to conceal its true identity.
  • D. isCostumedCharacterFor
    Indicates that one entity serves as a costumed character representation or mascot for another entity, typically for promotional or entertainment purposes.
  • E. characterAlias
    Indicates that one character is known or referred to by an alternative name or alias.
  • 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_69e77e82c9bc8190893090b2f6c64f1d completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f7221dc9a88190bb8194fcc29c42bc completed May 3, 2026, 10:23 a.m.
PD Predicate disambiguation batch_69f72153a9188190b02adc84e1be4af8 completed May 3, 2026, 10:20 a.m.
Created at: April 21, 2026, 8:49 p.m.