Triple

T14110941
Position Surface form Disambiguated ID Type / Status
Subject Lake Askoti E339631 entity
Predicate hasNearbyFeature P350 FINISHED
Object Lake Skannatati E438890 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: Lake Skannatati | Statement: [Lake Askoti, hasNearbyFeature, Lake Skannatati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Skannatati
Context triple: [Lake Askoti, hasNearbyFeature, Lake Skannatati]
  • A. Lake Skanatati chosen
    Lake Skanatati is a scenic freshwater lake in New York’s Harriman State Park, popular for fishing, hiking, and lakeside recreation.
  • B. Madawaska Lake
    Madawaska Lake is a small rural community and recreational area in Aroostook County, northern Maine, known for its lakeside camps, fishing, and outdoor activities.
  • C. Lake Waban
    Lake Waban is a scenic freshwater lake in Wellesley, Massachusetts, known for its walking trails and its central role in the landscape of Wellesley College.
  • D. Lake Absegami
    Lake Absegami is a recreational freshwater lake in New Jersey known for swimming, boating, and fishing within the Bass River State Forest.
  • E. Lake Skenonto
    Lake Skenonto is a scenic backcountry lake in New York’s Harriman State Park, popular with hikers and campers for its remote, forested setting.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de600e6a688190a1243a30ae9b7157 completed April 14, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7e04184819081633f9cfc0ccab9 completed May 7, 2026, 8:36 p.m.
Created at: April 9, 2026, 10:22 p.m.