Triple

T5192551
Position Surface form Disambiguated ID Type / Status
Subject Knockturn Alley area E117190 entity
Predicate fictionalSettingDepicted P26457 FINISHED
Object Knockturn Alley in London 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: Knockturn Alley in London | Statement: [Knockturn Alley area, fictionalSettingDepicted, Knockturn Alley in London]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalSettingDepicted
Context triple: [Knockturn Alley area, fictionalSettingDepicted, Knockturn Alley in London]
  • A. fictionalUniverseLocation chosen
    Indicates that one entity is a location or setting within the fictional universe to which the other entity belongs or in which it takes place.
  • B. setInFictionalLocation
    Indicates that an event, story, or narrative takes place within a fictional or imagined location rather than a real-world setting.
  • C. basedInFictionalLocation
    Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
  • D. hasFictionalLocation
    Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
  • E. placeOfSetting
    Indicates the location or environment where an event, scene, or situation takes place.
  • 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_69bd4462ed04819084fcb01eb9d2fa74 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79efd16c8190b0b16278a00baecd completed March 20, 2026, 4:46 p.m.
PD Predicate disambiguation batch_69bd77b7e8b4819092ec3965e11f2dea completed March 20, 2026, 4:37 p.m.
Created at: March 20, 2026, 1:46 p.m.