Triple

T31616835
Position Surface form Disambiguated ID Type / Status
Subject Jordan Lyman E806779 entity
Predicate hasFictionalSecurityDetail P197328 FINISHED
Object United States Secret Service 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: United States Secret Service | Statement: [Jordan Lyman, hasFictionalSecurityDetail, United States Secret Service]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFictionalSecurityDetail
Context triple: [Jordan Lyman, hasFictionalSecurityDetail, United States Secret Service]
  • A. hasFictionalSpy
    Indicates that an entity includes, features, or is associated with a fictional spy character.
  • B. fictionalSecurityLevel
    Indicates the degree or category of security status assigned within a fictional or imagined context.
  • C. hasFictionalProperty
    Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
  • D. hasFictionalContent
    Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
  • E. hasFictionalDocument
    Indicates that one entity possesses, is associated with, or includes a document that is fictional or exists only within an imagined or narrative context.
  • 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_69f348d61f2081908cad94bc9ffbb671 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69fe87b609888190913b0c3f787ecdba completed May 9, 2026, 1:02 a.m.
PD Predicate disambiguation batch_69fe8731af48819092084f6f74bf052d completed May 9, 2026, 1 a.m.
PDg Predicate description generation batch_69fe87b52bd4819087d6d338fe47c97c completed May 9, 2026, 1:02 a.m.
Created at: April 30, 2026, 10:39 p.m.