Triple

T4841762
Position Surface form Disambiguated ID Type / Status
Subject Lumen in caelo E108193 entity
Predicate hasPart P35 FINISHED
Object Lumen
Lumen is a character or element from the work "Lumen in caelo," likely serving as a central or significant figure within that context.
 E473642 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: Lumen | Statement: [Lumen in caelo, hasPart, Lumen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lumen
Context triple: [Lumen in caelo, hasPart, Lumen]
  • A. Lumen
    Lumen is a lightweight PHP micro-framework created by the Laravel team, optimized for building fast microservices and APIs.
  • B. Lumen
    Lumen is a telecommunications and technology company brand offering network, edge cloud, security, and communication services to businesses and enterprises.
  • C. Luma
    Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
  • D. Illumination
    Illumination is an American animation studio best known for creating the Despicable Me franchise and other popular family-oriented animated films.
  • E. Lumo
    Lumo is a British open-access train operator running low-cost, long-distance electric services on the East Coast Main Line between London and northeastern England.
  • 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: Lumen
Triple: [Lumen in caelo, hasPart, Lumen]
Generated description
Lumen is a character or element from the work "Lumen in caelo," likely serving as a central or significant figure within that context.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lumen
Target entity description: Lumen is a character or element from the work "Lumen in caelo," likely serving as a central or significant figure within that context.
  • A. Lumen
    Lumen is a telecommunications and technology company brand offering network, edge cloud, security, and communication services to businesses and enterprises.
  • B. Lumen
    Lumen is a lightweight PHP micro-framework created by the Laravel team, optimized for building fast microservices and APIs.
  • C. Luma
    Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
  • D. Illumination
    Illumination is an American animation studio best known for creating the Despicable Me franchise and other popular family-oriented animated films.
  • E. Lumo
    Lumo is a British open-access train operator running low-cost, long-distance electric services on the East Coast Main Line between London and northeastern England.
  • 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_69bd4409b264819085ab855f3eb5381a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6cfd9f3c8190b2b4edb05e9a5d33 completed March 20, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5ccdf7a081909624f5cff787e688 completed March 21, 2026, 8:54 a.m.
NEDg Description generation batch_69be5dbb7abc819096f55477cab2d408 completed March 21, 2026, 8:58 a.m.
NED2 Entity disambiguation (via description) batch_69be5e8540688190a6e475e128d79d2b completed March 21, 2026, 9:01 a.m.
Created at: March 20, 2026, 1:25 p.m.