Triple

T16295886
Position Surface form Disambiguated ID Type / Status
Subject Taylor Dearden E395645 entity
Predicate familyName P18 FINISHED
Object Dearden E1049898 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: Dearden | Statement: [Taylor Dearden, familyName, Dearden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dearden
Context triple: [Taylor Dearden, familyName, Dearden]
  • A. Dearden chosen
    Dearden is an English surname borne by various notable individuals across fields such as film, politics, and academia.
  • B. Sharswood
    Sharswood is a residential neighborhood in North Philadelphia known for its ongoing redevelopment and proximity to areas like Brewerytown and Girard College.
  • C. Burdine
    Burdine is the respondent in the U.S. Supreme Court employment discrimination case Texas Department of Community Affairs v. Burdine, which clarified the burden of proof framework in Title VII disparate treatment claims.
  • D. Goldwyn
    Goldwyn is a notable American surname most famously associated with film producer Samuel Goldwyn and his entertainment-industry family.
  • E. Thorton
    Thorton is a budget-oriented AMD Sempron CPU core derived from the Barton architecture, typically featuring a reduced L2 cache for lower-cost desktop processors.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e25e2d08108190bab1b3325923af1d completed April 17, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f9b42248190a3c8c2647a42aeb9 completed May 10, 2026, 6:03 a.m.
Created at: April 10, 2026, 5:06 a.m.