Triple

T17240731
Position Surface form Disambiguated ID Type / Status
Subject Mount Frissell E418489 entity
Predicate hasHighestPointOf P1674 FINISHED
Object Connecticut E10549 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: Connecticut | Statement: [Mount Frissell, hasHighestPointOf, Connecticut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Connecticut
Context triple: [Mount Frissell, hasHighestPointOf, Connecticut]
  • A. Connecticut chosen
    Connecticut is a small New England state in the northeastern United States known for its colonial history, affluent suburbs, and role as a financial and educational hub.
  • B. D. Conn.
    D. Conn. is the standard legal abbreviation for the United States District Court for the District of Connecticut, a federal trial court within the Second Circuit.
  • C. Rhoda Island
    Rhoda Island is a Nile island in central Cairo, Egypt, known for its historic palaces, gardens, and cultural landmarks.
  • D. Georgia, Vermont
    Georgia, Vermont is a small rural town in northwestern Vermont known for its agricultural landscape and proximity to Lake Champlain.
  • E. Vermont
    Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e203ec88190a21f38cbb18a14fa completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01793efa288190b63f641381566bb9 completed May 11, 2026, 6:37 a.m.
Created at: April 10, 2026, 5:39 a.m.