Triple

T5688948
Position Surface form Disambiguated ID Type / Status
Subject Hoosier National Forest region E125380 entity
Predicate hasNearbyTownType P65946 FINISHED
Object historic resort towns 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: historic resort towns | Statement: [Hoosier National Forest region, hasNearbyTownType, historic resort towns]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNearbyTownType
Context triple: [Hoosier National Forest region, hasNearbyTownType, historic resort towns]
  • A. hasNearbyTown
    Indicates that one location has a town situated close to it in geographic proximity.
  • B. hasTribalHeadquartersNearby
    Indicates that the subject entity is located close to the tribal headquarters of a Native nation or tribe.
  • C. hasNearestLargerSettlement
    Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
  • D. hasNearbyHabitats
    Indicates that one entity has other habitats located close to it in geographic or spatial terms.
  • E. hasNearbyAncientCity
    Indicates that one entity is located close to another entity that is classified as an ancient city.
  • 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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029014588819094a2a0f6f9b66bab completed March 22, 2026, 5:38 p.m.
PD Predicate disambiguation batch_69c021c0e0408190ab6c3cd3f907e80f completed March 22, 2026, 5:07 p.m.
PDg Predicate description generation batch_69c028fec2bc819083f5dca6a8d9d435 completed March 22, 2026, 5:38 p.m.
Created at: March 22, 2026, 3:44 p.m.