Triple

T26699331
Position Surface form Disambiguated ID Type / Status
Subject USS Miller (FF-1091) E673106 entity
Predicate namesakeDistinction P161134 FINISHED
Object first African American to receive the Navy Cross LITERAL 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: first African American to receive the Navy Cross | Statement: [USS Miller (FF-1091), namesakeDistinction, first African American to receive the Navy Cross]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: namesakeDistinction
Context triple: [USS Miller (FF-1091), namesakeDistinction, first African American to receive the Navy Cross]
  • A. nameDistinction
    Indicates that two entities are distinguished from one another specifically by differences in their names.
  • B. namesakeDescription
    Indicates that the object provides a descriptive explanation of why or how the subject is considered a namesake of something or someone.
  • C. namesakeNationality
    Indicates that one entity has the same nationality as the person or entity after whom it is named.
  • D. namesakeFamily
    Indicates that one entity is a family or familial group that shares the same name as, or is named after, another entity.
  • E. namesakeType
    Indicates the specific kind or category of namesake relationship that exists between two entities (for example, one being named after the other as a person, place, event, or object).
  • F. None of above. chosen

Provenance (4 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_69eecda2b49c8190a6c481cfc4c07954 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6177e2870819092bd441b95a21223 completed May 2, 2026, 3:25 p.m.
PD Predicate disambiguation batch_69f60b8bb0d08190ab5a9a2a8847c6f4 completed May 2, 2026, 2:34 p.m.
PDg Predicate description generation batch_69f60f24ed608190bffe6c6084fc2f7a completed May 2, 2026, 2:50 p.m.
Created at: April 27, 2026, 3:30 a.m.