Triple

T2705978
Position Surface form Disambiguated ID Type / Status
Subject Sun–Earth L2 E59342 entity
Predicate label P38 FINISHED
Object L2
L2 is the second Sun–Earth Lagrange point, a gravitationally stable location in space used by space telescopes such as the James Webb Space Telescope for observation.
 E290065 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: L2 | Statement: [Sun–Earth L2, label, L2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: L2
Context triple: [Sun–Earth L2, label, L2]
  • A. L2M
    L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. L
    L is the vehicle registration code used on license plates for the German city and district of Leipzig.
  • 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: L2
Triple: [Sun–Earth L2, label, L2]
Generated description
L2 is the second Sun–Earth Lagrange point, a gravitationally stable location in space used by space telescopes such as the James Webb Space Telescope for observation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: L2
Target entity description: L2 is the second Sun–Earth Lagrange point, a gravitationally stable location in space used by space telescopes such as the James Webb Space Telescope for observation.
  • A. L2M
    L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. L
    L is the vehicle registration code used on license plates for the German city and district of Leipzig.
  • 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_69ab4ac66bc88190b9e4afa5fc843f72 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda559a908190ad5d92c11a398a03 completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf7c22a4819096ff9effe9e0d77d completed March 10, 2026, 5:43 a.m.
NEDg Description generation batch_69afb039cdcc8190953368c1f6757503 completed March 10, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69afb0c27ee48190a319fd2fab02f755 completed March 10, 2026, 5:48 a.m.
Created at: March 6, 2026, 9:55 p.m.