Triple

T8663110
Position Surface form Disambiguated ID Type / Status
Subject Collins Center for the Arts E205595 entity
Predicate namedAfter P63 FINISHED
Object Susan Collins E399605 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: Susan Collins | Statement: [Collins Center for the Arts, namedAfter, Susan Collins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susan Collins
Context triple: [Collins Center for the Arts, namedAfter, Susan Collins]
  • A. Susan Collins chosen
    Susan Collins is a long-serving Republican U.S. senator from Maine known for her moderate positions and influential swing votes on key legislation.
  • B. Olympia Snowe
    Olympia Snowe is a former U.S. Senator from Maine known for her moderate Republican views and bipartisan legislative approach.
  • C. Kay Bailey Hutchison
    Kay Bailey Hutchison is an American attorney and Republican politician who served as a long-time U.S. Senator from Texas.
  • D. Sarah Palin
    Sarah Palin is an American politician and former governor of Alaska who gained national prominence as the Republican vice-presidential nominee in the 2008 U.S. presidential election.
  • E. Mari Blanchard
    Mari Blanchard was an American film and television actress of the 1950s and 1960s, known for her roles in Westerns and adventure films.
  • 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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4872a190819087d679f3006bd030 completed March 31, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecd0518248190ba0d3a87d11dff86 completed April 2, 2026, 8:09 p.m.
Created at: March 30, 2026, 6:30 p.m.