Triple

T746170
Position Surface form Disambiguated ID Type / Status
Subject Hull, Iowa E15345 entity
Predicate hasRegionCode P3446 FINISHED
Object US-IA E15939 NE 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: US-IA | Statement: [Hull, Iowa, hasRegionCode, US-IA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: US-IA
Context triple: [Hull, Iowa, hasRegionCode, US-IA]
  • A. Iowa chosen
    Iowa is a Midwestern U.S. state known for its extensive agriculture, especially corn and soybean production, and its role in national politics through the Iowa caucuses.
  • B. Illinois
    Illinois is a Midwestern U.S. state known for its major metropolis Chicago, diverse economy, and significant political and transportation influence.
  • C. Indiana
    Indiana is a U.S. state known for its manufacturing base, rich agricultural land, and iconic events like the Indianapolis 500.
  • D. US-MS
    US-MS is the ISO 3166-2 code representing the U.S. state of Mississippi.
  • E. Wisconsin
    Wisconsin is a U.S. state in the Upper Midwest known for its dairy industry, Great Lakes shorelines, and mix of rural landscapes and industrial cities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a62ca1d081908e3191411f86498d completed March 1, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69a654e664e4819081badaf0ba0d86e5 completed March 3, 2026, 3:26 a.m.
Created at: March 1, 2026, 7:37 p.m.