Triple

T20257669
Position Surface form Disambiguated ID Type / Status
Subject The Loyal Eddies E498746 entity
Predicate abbreviation P43 FINISHED
Object LER
LER is the abbreviation for The Loyal Eddies, a group or organization likely centered around shared loyalty or fandom, often in a sports or community context.
 E1420836 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: LER | Statement: [The Loyal Eddies, abbreviation, LER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LER
Context triple: [The Loyal Eddies, abbreviation, LER]
  • A. LER
    LER is the vehicle registration code assigned to the German island municipality of Borkum.
  • B. LER
    LER is the National Rail station code for Leytonstone High Road railway station in London.
  • C. LR
    LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
  • D. LR
    LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
  • E. LR
    LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
  • 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: LER
Triple: [The Loyal Eddies, abbreviation, LER]
Generated description
LER is the abbreviation for The Loyal Eddies, a group or organization likely centered around shared loyalty or fandom, often in a sports or community context.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LER
Target entity description: LER is the abbreviation for The Loyal Eddies, a group or organization likely centered around shared loyalty or fandom, often in a sports or community context.
  • A. LER
    LER is the vehicle registration code assigned to the German island municipality of Borkum.
  • B. LER
    LER is the National Rail station code for Leytonstone High Road railway station in London.
  • C. LR
    LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
  • D. LR
    LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
  • E. LR
    LR is the commonly used abbreviation for Les Républicains, a major center-right political party in France.
  • 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e674c7296c819092860942de8f28d5 completed April 20, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08552c65488190922fc54374072e69 completed May 16, 2026, 11:29 a.m.
NEDg Description generation batch_6a0855d7d87481908ff14d53a2ac94f7 completed May 16, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a0856da3e748190866c328a6c61b3d8 completed May 16, 2026, 11:36 a.m.
Created at: April 11, 2026, 11:41 p.m.