Triple

T21353260
Position Surface form Disambiguated ID Type / Status
Subject Wayne County, Kentucky E526542 entity
Predicate hasCountyNumberInKentucky P143960 FINISHED
Object 95 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: 95 | Statement: [Wayne County, Kentucky, hasCountyNumberInKentucky, 95]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCountyNumberInKentucky
Context triple: [Wayne County, Kentucky, hasCountyNumberInKentucky, 95]
  • A. hasCountyNumberInKansas
    Indicates that an entity is assigned a specific official county number within the state of Kansas.
  • B. hasCountyNumberInIndiana
    Indicates that a county is associated with its designated county number within the state of Indiana.
  • C. hasCountyNumberInTennessee
    Indicates that an entity is assigned a specific official county number within the state of Tennessee.
  • D. hasCountyNumberInArkansas
    Indicates that an entity is assigned a specific official county number within the state of Arkansas.
  • E. hasCountyCode
    Indicates that an entity is associated with a specific county identified by a standardized county code.
  • 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5bab98148190aa14d52fd37bc894 completed April 26, 2026, 6:38 p.m.
PD Predicate disambiguation batch_69e6162bbfc88190a3e75859941b2638 completed April 20, 2026, 12:03 p.m.
PDg Predicate description generation batch_69e61b3e47f881908fb2aac9bd2bfb58 completed April 20, 2026, 12:25 p.m.
Created at: April 16, 2026, 5:05 p.m.