Triple

T22802642
Position Surface form Disambiguated ID Type / Status
Subject Anna Myrtle Swoyer E564438 entity
Predicate familyName P18 FINISHED
Object Swoyer NE NERFINISHED

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: Swoyer | Statement: [Anna Myrtle Swoyer, familyName, Swoyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swoyer
Context triple: [Anna Myrtle Swoyer, familyName, Swoyer]
  • A. Swoyer chosen
    Swoyer is a surname associated with individuals such as Nancy Walker.
  • B. Sawyer
    Sawyer is a surname of English origin commonly borne by individuals in English-speaking countries.
  • C. Sawyer
    Sawyer is a collaborative industrial robot arm developed by Rethink Robotics for flexible, safe automation tasks alongside human workers.
  • D. Sawyer Valentini
    Sawyer Valentini is the troubled young woman at the center of the psychological horror film "Unsane," whose involuntary commitment to a mental institution blurs the line between paranoia and reality.
  • E. Parker Sawyers
    Parker Sawyers is an American actor best known for portraying a young Barack Obama in the film "Southside with You" and for his work in various international film and television productions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245823f4c8190ade442cdcc2c224a completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17cdf1e308190a05d0f61856be544 completed April 29, 2026, 3:37 a.m.
Created at: April 17, 2026, 3:31 p.m.