Triple

T15689136
Position Surface form Disambiguated ID Type / Status
Subject Laramie E380278 entity
Predicate typicalSafetyFeatures P5084 FINISHED
Object multiple airbags 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: multiple airbags | Statement: [Laramie, typicalSafetyFeatures, multiple airbags]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalSafetyFeatures
Context triple: [Laramie, typicalSafetyFeatures, multiple airbags]
  • A. hasSafetyCharacteristic
    Indicates that an entity possesses a specific safety-related property, feature, or attribute.
  • B. typicalFeatures chosen
    Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
  • C. securityFeature
    Indicates that an entity provides, embodies, or is associated with a mechanism or property intended to enhance safety, protection, or defense against threats or vulnerabilities.
  • D. safetyRatingHighlight
    Indicates that an entity’s safety rating is emphasized or specially marked as noteworthy compared to others.
  • E. chassisFeature
    Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4cee5481908699fbb2b7bdd2f6 completed April 16, 2026, 2:54 a.m.
PD Predicate disambiguation batch_69deda8c856c8190882330114f9a1a5f completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:44 a.m.