Triple

T3802038
Position Surface form Disambiguated ID Type / Status
Subject Maxus E91709 entity
Predicate brandPredecessor P1501 FINISHED
Object LDV
LDV was a British commercial vehicle manufacturer best known for producing vans and minibuses, particularly for business and fleet use.
E388721 NE FINISHED

How this triple was built (5 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: LDV | Statement: [Maxus, brandPredecessor, LDV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LDV
Context triple: [Maxus, brandPredecessor, LDV]
  • A. LEVD
    LEVD is the ICAO airport code assigned to Valladolid Airport in Spain.
  • B. LSV
    LSV is the IATA airport code for the military airfield serving Nellis Air Force Base near Las Vegas, Nevada.
  • C. LD
    LD is the IATA airline designator assigned to Air Hong Kong, a cargo airline based in Hong Kong.
  • D. LRD
    LRD is the official currency code for the Liberian dollar, the legal tender used in Liberia.
  • E. LDF
    LDF is a prominent U.S. civil rights law organization that litigates and advocates to advance racial justice and equality, particularly for African Americans.
  • 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: LDV
Triple: [Maxus, brandPredecessor, LDV]
Generated description
LDV was a British commercial vehicle manufacturer best known for producing vans and minibuses, particularly for business and fleet use.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LDV
Target entity description: LDV was a British commercial vehicle manufacturer best known for producing vans and minibuses, particularly for business and fleet use.
  • A. LEVD
    LEVD is the ICAO airport code assigned to Valladolid Airport in Spain.
  • B. LSV
    LSV is the IATA airport code for the military airfield serving Nellis Air Force Base near Las Vegas, Nevada.
  • C. LD
    LD is the IATA airline designator assigned to Air Hong Kong, a cargo airline based in Hong Kong.
  • D. LRD
    LRD is the official currency code for the Liberian dollar, the legal tender used in Liberia.
  • E. LDF
    LDF is a prominent U.S. civil rights law organization that litigates and advocates to advance racial justice and equality, particularly for African Americans.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: brandPredecessor
Context triple: [Maxus, brandPredecessor, LDV]
  • A. predecessorFranchise
    Indicates that one franchise directly precedes and is succeeded by another franchise in a series or lineage.
  • B. formerBrand chosen
    Indicates that an entity was previously used or recognized as a brand for another entity but is no longer its current brand.
  • C. predecessorSystem
    Indicates that one system existed or was in use before and was replaced or superseded by another system.
  • D. predecessorName
    Indicates that the value is the name of an entity that directly precedes another in an ordered sequence or lineage.
  • E. successorBranding
    Indicates that one brand has replaced or continued another brand as its subsequent or updated identity.
  • F. None of above.

Provenance (6 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_69aed96354f48190a768966d6bd19b04 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee8db8a288190afd1e3b9dcf02e97 completed March 9, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f066e30481909e5baa630f3539e4 completed March 14, 2026, 5:21 a.m.
NEDg Description generation batch_69b4f21d7410819084b521a7c4a4b151 completed March 14, 2026, 5:29 a.m.
NED2 Entity disambiguation (via description) batch_69b4f275d18c81909e93a6ff11fa66b4 completed March 14, 2026, 5:30 a.m.
PD Predicate disambiguation batch_69aee7461abc8190945716f4b93e1a18 completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:15 p.m.