Triple

T15082509
Position Surface form Disambiguated ID Type / Status
Subject Bundanoon E360183 entity
Predicate nearbyTown P3883 FINISHED
Object Sutton Forest E1120829 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: Sutton Forest | Statement: [Bundanoon, nearbyTown, Sutton Forest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sutton Forest
Context triple: [Bundanoon, nearbyTown, Sutton Forest]
  • A. Sutton Forest chosen
    Sutton Forest is a small rural village in the Southern Highlands of New South Wales, Australia, known for its historic estates, cool climate, and pastoral landscapes.
  • B. Swinley Forest
    Swinley Forest is a large coniferous woodland and popular outdoor recreation area in Berkshire, England, known for its mountain biking trails, walking paths, and wildlife.
  • C. Ashdown Forest
    Ashdown Forest is a historic heathland and woodland area in East Sussex, England, famed as the inspiration for A.A. Milne’s Winnie-the-Pooh stories.
  • D. Knettishall Heath
    Knettishall Heath is a large nature reserve in Suffolk, England, known for its heathland, woodland, and rich wildlife habitats.
  • E. Dunn Forest
    Dunn Forest is a component of Oregon State University's McDonald-Dunn Research Forest, used primarily for forestry research, education, and sustainable land management.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0027450a48190a84588b6aaf84ebf completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae179a24819097019976707c93e1 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:03 a.m.