Triple

T15402040
Position Surface form Disambiguated ID Type / Status
Subject Lake County, Minnesota E368343 entity
Predicate U.S. state FIPS code P227 FINISHED
Object 27 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: 27 | Statement: [Lake County, Minnesota, U.S. state FIPS code, 27]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: U.S. state FIPS code
Context triple: [Lake County, Minnesota, U.S. state FIPS code, 27]
  • A. FIPSCode chosen
    Indicates the standardized Federal Information Processing Standards (FIPS) code assigned to identify a specific geographic or administrative entity.
  • B. FIPSCountryCode
    Indicates that an entity is associated with a specific country as identified by its FIPS (Federal Information Processing Standards) country code.
  • C. federalStateCode
    Indicates that an entity is associated with, governed by, or identified through a specific federal state code within a country’s administrative or legal system.
  • D. FISCode
    Indicates a standardized financial institution identifier code used to uniquely reference a specific bank or financial entity in transactions or records.
  • E. keyUSState
    Indicates that a U.S. state plays a primary or strategically important role in a given context (such as politics, economy, or policy).
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e8ea0ac8190a5c68b1951ad3db1 completed April 16, 2026, 1:42 a.m.
PD Predicate disambiguation batch_69ded27b8cac8190bfa77698d53c5d1c completed April 14, 2026, 11:49 p.m.
Created at: April 10, 2026, 3:19 a.m.