Triple

T16671364
Position Surface form Disambiguated ID Type / Status
Subject Walden Woods Project E405111 entity
Predicate namedAfter P63 FINISHED
Object Walden Woods E1227259 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: Walden Woods | Statement: [Walden Woods Project, namedAfter, Walden Woods]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walden Woods
Context triple: [Walden Woods Project, namedAfter, Walden Woods]
  • A. Walden Woods chosen
    Walden Woods is the forested area in Concord, Massachusetts, made famous by Henry David Thoreau’s book "Walden" and recognized as an important site for American literary and environmental history.
  • B. Prouty Woods
    Prouty Woods is a protected natural area in Littleton, Massachusetts, known for its forests, trails, and open space for outdoor recreation and wildlife habitat.
  • C. Peirce’s Woods
    Peirce’s Woods was the historic arboreal tract in Pennsylvania that later became part of the renowned Longwood Gardens estate.
  • D. Stearns Woods
    Stearns Woods is a local natural park and wooded recreation area located in Wyoming, Ohio.
  • E. Vergible Woods
    Vergible Woods, better known as Tea Cake, is a central character and Janie's charismatic third husband in Zora Neale Hurston's novel "Their Eyes Were Watching God."
  • 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_69d8838b5fbc81908c6575c132b82e80 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ca175088190a0435422e13278c2 completed April 18, 2026, 12:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d31372c8190b9d73a9b7db51f0f completed May 10, 2026, 2:58 p.m.
Created at: April 10, 2026, 5:18 a.m.