Triple

T30098155
Position Surface form Disambiguated ID Type / Status
Subject Sir Boss E764921 entity
Predicate timeDisplacementFrom P10439 FINISHED
Object 19th-century United States 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: 19th-century United States | Statement: [Sir Boss, timeDisplacementFrom, 19th-century United States]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: timeDisplacementFrom
Context triple: [Sir Boss, timeDisplacementFrom, 19th-century United States]
  • A. timeDisplacedTo
    Indicates that one entity has been moved or transported from its original temporal position to a different point in time relative to another entity or reference time.
  • B. timeEquivalentOf
    Indicates that two temporal entities represent the same point in time or duration, possibly expressed in different formats or units.
  • C. timeTravelFrom chosen
    Indicates a relationship where an entity initiates time travel starting from a specific time or temporal location.
  • D. timeDifferenceWith
    Indicates a relationship where the temporal difference or interval between two time points, events, or entities is specified or measured.
  • E. timeBehind
    Indicates that one entity occurs or is positioned later in time than another, lagging behind it on a temporal scale.
  • F. None of above.

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_69f22474e4288190b5f895fe3974aa92 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67d92dbdc8190ae3e8f67b979cb5c completed May 2, 2026, 10:41 p.m.
PD Predicate disambiguation batch_69f673c664f08190b4d66cdc305e10db completed May 2, 2026, 9:59 p.m.
Created at: April 29, 2026, 7:07 p.m.