Triple

T136482
Position Surface form Disambiguated ID Type / Status
Subject Detroit Big Three automakers E2757 entity
Predicate historicallySpecializedIn P466 FINISHED
Object large vehicles 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: large vehicles | Statement: [Detroit Big Three automakers, historicallySpecializedIn, large vehicles]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: historicallySpecializedIn
Context triple: [Detroit Big Three automakers, historicallySpecializedIn, large vehicles]
  • A. historicallyBorneBy
    Indicates that an entity has carried, possessed, or used another entity (such as a name, title, or symbol) at some point in the past.
  • B. hasSpecialty chosen
    Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
  • C. historicallyUsedFor
    Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
  • D. historicallyPrizedFor
    Indicates that something has been especially valued or esteemed for a particular quality, use, or significance in the past.
  • E. historicallyExtendedBy
    Indicates that something has been continued, expanded, or carried forward over time by another, later entity or development.
  • 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_69a2520c0f3481908b0ed054a2fca8d0 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a257a4edf081908c494c8370c76b9a completed Feb. 28, 2026, 2:49 a.m.
PD Predicate disambiguation batch_69a25652efdc8190b85b33735a9e6370 completed Feb. 28, 2026, 2:43 a.m.
Created at: Feb. 28, 2026, 2:30 a.m.