Triple

T1096158
Position Surface form Disambiguated ID Type / Status
Subject LEP E24275 entity
Predicate hostedExperiment P1591 FINISHED
Object 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.
 E127242 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 | Statement: [LEP, hostedExperiment, L3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: L3
Context triple: [LEP, hostedExperiment, L3]
  • A. L
    L is the enigmatic, emotionally complex protagonist of Hanne Ørstavik’s novel "Love," whose inner life and perspective drive the story’s exploration of isolation and longing.
  • B. L
    The L is a Chicago 'L' rapid transit line that serves the city’s West Side and western suburbs as part of the Chicago Transit Authority system.
  • C. LV
    LV is the two-letter ISO 3166-1 alpha-2 country code representing Latvia.
  • D. L2M
    L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
  • E. Line 3
    Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • 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
Triple: [LEP, hostedExperiment, L3]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: L3
Target entity description: 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.
  • A. L
    L is the enigmatic, emotionally complex protagonist of Hanne Ørstavik’s novel "Love," whose inner life and perspective drive the story’s exploration of isolation and longing.
  • B. L
    The L is a Chicago 'L' rapid transit line that serves the city’s West Side and western suburbs as part of the Chicago Transit Authority system.
  • C. LV
    LV is the two-letter ISO 3166-1 alpha-2 country code representing Latvia.
  • D. L2M
    L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
  • E. Line 3
    Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • 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_69a4940542308190ac2a0b1f730b7cfc completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bb74b0908190be51a7141e661d3e completed March 1, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c3bb31881908768a909ce56a95d completed March 7, 2026, 4:03 p.m.
NEDg Description generation batch_69ac5020f5748190b89c938240e63637 completed March 7, 2026, 4:19 p.m.
NED2 Entity disambiguation (via description) batch_69ac50a982748190964d4fbef332baa5 completed March 7, 2026, 4:22 p.m.
Created at: March 1, 2026, 7:42 p.m.