Triple

T14514960
Position Surface form Disambiguated ID Type / Status
Subject Fiat-Ansaldo L3 series E340492 entity
Predicate hasVariant P455 FINISHED
Object L3/33
The L3/33 was an Italian interwar light tankette used primarily for reconnaissance and infantry support roles before and during the early stages of World War II.
 E1103329 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: L3/33 | Statement: [Fiat-Ansaldo L3 series, hasVariant, L3/33]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: L3/33
Context triple: [Fiat-Ansaldo L3 series, hasVariant, L3/33]
  • A. L3
    L3 is a particle physics experiment that operated at CERN’s Large Electron–Positron Collider, designed to study high-energy electron–positron collisions and probe the Standard Model.
  • B. L3
    L3 is one of the main lines of the Barcelona Metro rapid transit system.
  • C. L83
    L83 is a 5.3-liter GM EcoTec3 V8 truck engine used in late-model Chevrolet and GMC pickups and SUVs.
  • D. F33
    F33 is BMW’s internal designation for the first-generation 4 Series convertible model.
  • E. D33
    D33 is a prehistoric megalithic tomb (hunebed) located in the municipality of Aa en Hunze in the Netherlands.
  • 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: L3/33
Triple: [Fiat-Ansaldo L3 series, hasVariant, L3/33]
Generated description
The L3/33 was an Italian interwar light tankette used primarily for reconnaissance and infantry support roles before and during the early stages of World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: L3/33
Target entity description: The L3/33 was an Italian interwar light tankette used primarily for reconnaissance and infantry support roles before and during the early stages of World War II.
  • A. L3
    L3 is a particle physics experiment that operated at CERN’s Large Electron–Positron Collider, designed to study high-energy electron–positron collisions and probe the Standard Model.
  • B. L3
    L3 is one of the main lines of the Barcelona Metro rapid transit system.
  • C. L83
    L83 is a 5.3-liter GM EcoTec3 V8 truck engine used in late-model Chevrolet and GMC pickups and SUVs.
  • D. F33
    F33 is BMW’s internal designation for the first-generation 4 Series convertible model.
  • E. D33
    D33 is a prehistoric megalithic tomb (hunebed) located in the municipality of Aa en Hunze in the Netherlands.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a6d82988190b6f957012bcc63d4 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6da64db881909a4f88d18031cb0c completed May 8, 2026, 4:59 a.m.
NEDg Description generation batch_69fd6f82453481909a3e1b032f30a7a5 completed May 8, 2026, 5:07 a.m.
NED2 Entity disambiguation (via description) batch_69fd708521c881909863b7cd3fc4a313 completed May 8, 2026, 5:11 a.m.
Created at: April 10, 2026, 1:21 a.m.