Triple

T1058596
Position Surface form Disambiguated ID Type / Status
Subject William O. Douglas E22853 entity
Predicate placeOfBirth P1 FINISHED
Object Maine, Minnesota, United States E29256 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: Maine, Minnesota, United States | Statement: [William O. Douglas, placeOfBirth, Maine, Minnesota, United States]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maine, Minnesota, United States
Context triple: [William O. Douglas, placeOfBirth, Maine, Minnesota, United States]
  • A. Minnesota
    Minnesota is a U.S. state known for its numerous lakes, cold winters, and vibrant cultural and economic centers like Minneapolis–Saint Paul.
  • B. Maine chosen
    Maine is a northeastern U.S. state known for its rugged coastline, maritime history, and vast forested interior.
  • C. Maine
    Maine is a historical region in northwestern France that played a significant role in the medieval power struggles between the English and French crowns.
  • D. Mexico, Maine
    Mexico, Maine is a small town in Oxford County known historically as a mill and residential community closely linked with the neighboring industrial town of Rumford.
  • E. Strong, Maine
    Strong, Maine is a small rural town in western Maine known historically for its lumber and toothpick manufacturing industries.
  • 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_69a493dada0481909c43649f9843ea91 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8dc9e8c819099fbb192bcf80615 completed March 1, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1c8ee9dc8190b9f6a46841003e8a completed March 8, 2026, 6:51 a.m.
Created at: March 1, 2026, 7:42 p.m.