Triple

T16750852
Position Surface form Disambiguated ID Type / Status
Subject Washington Mountain Lake E407070 entity
Predicate locatedOnLandform P30683 FINISHED
Object October Mountain NE NERFINISHED

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: October Mountain | Statement: [Washington Mountain Lake, locatedOnLandform, October Mountain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: October Mountain
Context triple: [Washington Mountain Lake, locatedOnLandform, October Mountain]
  • A. October Mountain chosen
    October Mountain is the highest elevation in October Mountain State Forest, a prominent natural feature in the Berkshire region of western Massachusetts.
  • B. Gray Mountain
    Gray Mountain is a legal thriller novel by John Grisham that follows a young lawyer uncovering corruption and environmental crimes in a small Appalachian coal town.
  • C. Snowshoe Mountain
    Snowshoe Mountain is a major ski resort and year-round outdoor recreation destination located in the Allegheny Mountains of West Virginia.
  • D. Ice Mountain
    Ice Mountain is a regional bottled water brand in the United States known for its spring water sourced from Midwestern aquifers.
  • E. Snow Mountain
    Snow Mountain is one of Taiwan’s highest and most prominent peaks, renowned for its alpine scenery and popular hiking routes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3aa271de48190b4a535408aeef734 completed April 18, 2026, 3:58 p.m.
Created at: April 10, 2026, 5:21 a.m.