Triple

T15710609
Position Surface form Disambiguated ID Type / Status
Subject Nico Muhly E380826 entity
Predicate placeOfBirth P1 FINISHED
Object Vermont E9978 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: Vermont | Statement: [Nico Muhly, placeOfBirth, Vermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vermont
Context triple: [Nico Muhly, placeOfBirth, Vermont]
  • A. Vermont chosen
    Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
  • B. Vermont
    Vermont is a small rural town located in Dane County, Wisconsin, known for its scenic landscapes and agricultural character.
  • C. Washington, Vermont
    Washington, Vermont is a small rural town in central Vermont known for its scenic landscapes and traditional New England character.
  • D. Georgia, Vermont
    Georgia, Vermont is a small rural town in northwestern Vermont known for its agricultural landscape and proximity to Lake Champlain.
  • E. New Hampshire
    New Hampshire is a small New England state in the northeastern United States known for its mountainous landscapes, early presidential primary, and “Live Free or Die” motto.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f8f5d6081908243fa59b46b7c76 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82f22fc88190820ecb171041136d completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:45 a.m.