Triple

T278494
Position Surface form Disambiguated ID Type / Status
Subject SA80 assault rifle E5300 entity
Predicate hasVariant P455 FINISHED
Object L86 LSW
The L86 LSW is the light support weapon variant of the British SA80 family, designed to provide sustained, accurate automatic fire at the squad level.
 E36251 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: L86 LSW | Statement: [SA80 assault rifle, hasVariant, L86 LSW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: L86 LSW
Context triple: [SA80 assault rifle, hasVariant, L86 LSW]
  • A. L2M
    L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
  • B. LNS
    LNS is the commonly used abbreviation for the Laboratory for Nuclear Science, a research institution focused on advancing the understanding of nuclear and particle physics.
  • C. SLV
    SLV is the three-letter ISO 3166-1 alpha-3 country code assigned to El Salvador.
  • D. LCC
    LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
  • E. LAS
    LAS is the commonly used abbreviation for the Arab League, a regional organization of Arab countries in and around North Africa, the Horn of Africa, and the Middle East.
  • 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: L86 LSW
Triple: [SA80 assault rifle, hasVariant, L86 LSW]
Generated description
The L86 LSW is the light support weapon variant of the British SA80 family, designed to provide sustained, accurate automatic fire at the squad level.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: L86 LSW
Target entity description: The L86 LSW is the light support weapon variant of the British SA80 family, designed to provide sustained, accurate automatic fire at the squad level.
  • A. L2M
    L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
  • B. LNS
    LNS is the commonly used abbreviation for the Laboratory for Nuclear Science, a research institution focused on advancing the understanding of nuclear and particle physics.
  • C. SLV
    SLV is the three-letter ISO 3166-1 alpha-3 country code assigned to El Salvador.
  • D. LCC
    LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
  • E. LAS
    LAS is the commonly used abbreviation for the Arab League, a regional organization of Arab countries in and around North Africa, the Horn of Africa, and the Middle East.
  • 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25dee7830819087f153769a8496b9 completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a394a2b1a081909bb78499544984da completed March 1, 2026, 1:21 a.m.
NEDg Description generation batch_69a3956f12208190bdfc4f265b712ce8 completed March 1, 2026, 1:25 a.m.
NED2 Entity disambiguation (via description) batch_69a395e03da8819095339cc6f9a230e4 completed March 1, 2026, 1:26 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.