Triple

T13874970
Position Surface form Disambiguated ID Type / Status
Subject First Lake E333556 entity
Predicate connectedTo P37 FINISHED
Object Second Lake E174877 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: Second Lake | Statement: [First Lake, connectedTo, Second Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Second Lake
Context triple: [First Lake, connectedTo, Second Lake]
  • A. Second Lake chosen
    Second Lake is one of the interconnected Adirondack lakes in New York’s Fulton Chain, popular for boating, fishing, and scenic recreation.
  • B. Third Lake
    Third Lake is one of the interconnected Adirondack lakes in New York’s Fulton Chain, known for recreational boating, fishing, and scenic forested shorelines.
  • C. Third Lake
    Third Lake is a small residential village in Lake County, Illinois, known for its suburban character and the lake that shares its name.
  • D. First Lake
    First Lake is a scenic Adirondack lake in Old Forge, New York, popular for boating, fishing, and tourism.
  • E. Fourth Lake
    Fourth Lake is a popular recreational lake in the central Adirondack region of New York, known for boating, fishing, and scenic mountain surroundings.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0be4031c8190bef5865ec23b18a0 completed April 14, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c109ac5c819090b2b7e43334f904 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.