Triple

T1284757
Position Surface form Disambiguated ID Type / Status
Subject Baojun E200 E27408 entity
Predicate safetyEquipment P26738 FINISHED
Object driver airbag 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: driver airbag | Statement: [Baojun E200, safetyEquipment, driver airbag]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: safetyEquipment
Context triple: [Baojun E200, safetyEquipment, driver airbag]
  • A. safety
    Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
  • B. safetyRequirement
    Indicates that one entity specifies or imposes conditions, standards, or measures necessary to ensure the safety of another entity or activity.
  • C. recommendedEquipment
    Indicates that one entity suggests or endorses another entity as suitable equipment to be used in a particular context or activity.
  • D. designedToWithstand
    Indicates that something has been intentionally created or engineered to resist, endure, or remain functional under specified conditions, forces, or stresses.
  • E. armourBelt
    Indicates a relationship where an armour belt is equipped on, attached to, or associated with an entity (such as a character, vehicle, or structure) as protective gear.
  • 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_69a496d4ec448190ad653b2590c46711 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b6dda48190a2e79084adea6ec1 completed March 1, 2026, 10:41 p.m.
PD Predicate disambiguation batch_69a4bee276d8819092f71c5a1140bb61 completed March 1, 2026, 10:34 p.m.
PDg Predicate description generation batch_69a4bf60545c8190901ccfb2cb7c4b41 completed March 1, 2026, 10:36 p.m.
Created at: March 1, 2026, 7:50 p.m.