Triple

T11907213
Position Surface form Disambiguated ID Type / Status
Subject Chester and Hester E283300 entity
Predicate inUniverseBusinessType P68868 FINISHED
Object roadside tourist attraction 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: roadside tourist attraction | Statement: [Chester and Hester, inUniverseBusinessType, roadside tourist attraction]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: inUniverseBusinessType
Context triple: [Chester and Hester, inUniverseBusinessType, roadside tourist attraction]
  • A. inUniverseType
    Indicates that one entity exists within, or is categorized as belonging to, a particular fictional or conceptual universe type defined by the other entity.
  • B. hasTypeOfBusinesses chosen
    Indicates that an entity is associated with or contains specific categories or kinds of businesses.
  • C. hasBusinessTypeAlong
    Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
  • D. inUniverseProductType
    Indicates that a product belongs to or is categorized within a specific fictional or defined universe or setting.
  • E. originalBusinessType
    Indicates the initial or primary category of business activity or industry classification associated with an entity before any subsequent changes or reclassifications.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e5264b2081909bda6c24abb89725 completed April 10, 2026, 11:55 a.m.
PD Predicate disambiguation batch_69d8bb3632ac8190b13e53c2b5db7125 completed April 10, 2026, 8:56 a.m.
Created at: April 8, 2026, 9:44 p.m.