Triple

T17611907
Position Surface form Disambiguated ID Type / Status
Subject Suzuki Equator E428982 entity
Predicate trimLevel P11486 FINISHED
Object RMZ-4
RMZ-4 is an off-road-oriented trim level of the Suzuki Equator pickup truck, featuring enhanced suspension and rugged styling.
E1277671 NE FINISHED

How this triple was built (4 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: RMZ-4 | Statement: [Suzuki Equator, trimLevel, RMZ-4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RMZ-4
Context triple: [Suzuki Equator, trimLevel, RMZ-4]
  • A. RMF Zecilie
    RMF Zecilie is a show jumping horse ridden in international competition by American equestrian Jessica Springsteen.
  • B. RM-422
    RM-422 is a regional road in the municipality of Abanilla, Spain, providing local transport connectivity within the area.
  • C. RZ
    RZ is the vehicle registration code used on license plates for the district of Lauenburg in the German state of Schleswig-Holstein.
  • D. RZO
    RZO is the ICAO airline designator used to identify Azores Airlines in international aviation operations.
  • E. GZM
    GZM is a major metropolitan area, often referring to the Upper Silesian–Zagłębie Metropolis in southern Poland, encompassing a large urban and industrial region.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: RMZ-4
Triple: [Suzuki Equator, trimLevel, RMZ-4]
Generated description
RMZ-4 is an off-road-oriented trim level of the Suzuki Equator pickup truck, featuring enhanced suspension and rugged styling.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: RMZ-4
Target entity description: RMZ-4 is an off-road-oriented trim level of the Suzuki Equator pickup truck, featuring enhanced suspension and rugged styling.
  • A. RMF Zecilie
    RMF Zecilie is a show jumping horse ridden in international competition by American equestrian Jessica Springsteen.
  • B. RM-422
    RM-422 is a regional road in the municipality of Abanilla, Spain, providing local transport connectivity within the area.
  • C. RZ
    RZ is the vehicle registration code used on license plates for the district of Lauenburg in the German state of Schleswig-Holstein.
  • D. RZO
    RZO is the ICAO airline designator used to identify Azores Airlines in international aviation operations.
  • E. GZM
    GZM is a major metropolitan area, often referring to the Upper Silesian–Zagłębie Metropolis in southern Poland, encompassing a large urban and industrial region.
  • F. None of above. chosen

Provenance (5 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d2dfa688190a0b9b396bb6133cc completed April 19, 2026, 5:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01e8241cb481909ebb91e24c6eaf63 completed May 11, 2026, 2:31 p.m.
NEDg Description generation batch_6a01ee1a291c81909fa432ccc787028f completed May 11, 2026, 2:56 p.m.
NED2 Entity disambiguation (via description) batch_6a01eec7e00c81908d88be9f88e924c8 completed May 11, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:51 a.m.