Triple

T9958560
Position Surface form Disambiguated ID Type / Status
Subject Angus King E195504 entity
Predicate precededBy P97 FINISHED
Object Olympia Snowe E195503 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: Olympia Snowe | Statement: [Angus King, precededBy, Olympia Snowe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olympia Snowe
Context triple: [Angus King, precededBy, Olympia Snowe]
  • A. Olympia Snowe chosen
    Olympia Snowe is a former U.S. Senator from Maine known for her moderate Republican views and bipartisan legislative approach.
  • B. Susan Collins
    Susan Collins is a long-serving Republican U.S. senator from Maine known for her moderate positions and influential swing votes on key legislation.
  • C. Sharon Jeffords
    Sharon Jeffords is a fictional character from the television sitcom "Brooklyn Nine-Nine," known as the supportive and strong-willed wife of Sergeant Terry Jeffords.
  • D. Patty Murray
    Patty Murray is a long-serving Democratic U.S. senator from Washington known for her leadership roles in the Senate and work on budget, education, and health policy.
  • E. Chellie Pingree
    Chellie Pingree is an American Democratic politician and U.S. Representative from Maine known for her work on environmental, agricultural, and campaign finance reform issues.
  • 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_69ca82eaaa008190a54fa1a9f954b9ad completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb6cec7dc8190bb7e43c82a317707 completed April 2, 2026, 12:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257aa73d4819081f77f8386449905 completed April 5, 2026, 12:38 p.m.
Created at: March 30, 2026, 8:46 p.m.