Triple

T1372009
Position Surface form Disambiguated ID Type / Status
Subject London King’s Cross E30132 entity
Predicate servedBy P82 FINISHED
Object 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.
 E158398 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: Lumo | Statement: [London King’s Cross, servedBy, Lumo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lumo
Context triple: [London King’s Cross, servedBy, Lumo]
  • A. 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.
  • B. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • C. Lampa
    Lampa is a commune and town in central Chile known for its semi-rural character and growing residential and industrial development near Santiago.
  • D. Blaze
    Blaze is the anthropomorphic orange cat mascot of the Portland Trail Blazers NBA team.
  • E. Illumination
    Illumination is an American animation studio best known for creating the Despicable Me franchise and other popular family-oriented animated films.
  • 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: Lumo
Triple: [London King’s Cross, servedBy, Lumo]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lumo
Target entity description: 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.
  • A. 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.
  • B. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • C. Lampa
    Lampa is a commune and town in central Chile known for its semi-rural character and growing residential and industrial development near Santiago.
  • D. Blaze
    Blaze is the anthropomorphic orange cat mascot of the Portland Trail Blazers NBA team.
  • E. Illumination
    Illumination is an American animation studio best known for creating the Despicable Me franchise and other popular family-oriented animated films.
  • 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c2f314c081909c0ab80397d96abb completed March 1, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd481de608190bed1dc385209320e completed March 8, 2026, 1:44 a.m.
NEDg Description generation batch_69acd6a03b70819096bdf7ec3b447756 completed March 8, 2026, 1:53 a.m.
NED2 Entity disambiguation (via description) batch_69acd71971448190940136b8a44040be completed March 8, 2026, 1:55 a.m.
Created at: March 1, 2026, 7:57 p.m.