Triple

T1306737
Position Surface form Disambiguated ID Type / Status
Subject LMA Manager of the Decade E27895 entity
Predicate presentedBy P83 FINISHED
Object LMA
LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
 E149289 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: LMA | Statement: [LMA Manager of the Decade, presentedBy, LMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LMA
Context triple: [LMA Manager of the Decade, presentedBy, LMA]
  • A. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • B. LIM
    LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
  • C. LM
    LM is the IATA airline designator assigned to Loganair, a regional airline based in Scotland.
  • D. LMT
    LMT is the stock ticker symbol for Lockheed Martin Corporation, a major American aerospace, defense, and security company.
  • E. HMA
    HMA is a European network of national medicines regulatory authorities that collaborates to ensure the quality, safety, and efficacy of medicinal products across member states.
  • 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: LMA
Triple: [LMA Manager of the Decade, presentedBy, LMA]
Generated description
LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LMA
Target entity description: LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
  • A. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • B. LIM
    LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
  • C. LM
    LM is the IATA airline designator assigned to Loganair, a regional airline based in Scotland.
  • D. LMT
    LMT is the stock ticker symbol for Lockheed Martin Corporation, a major American aerospace, defense, and security company.
  • E. HMA
    HMA is a European network of national medicines regulatory authorities that collaborates to ensure the quality, safety, and efficacy of medicinal products across member states.
  • 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_69a496d7d83481908f83085854e51328 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c1368038819089d1091cc43901a3 completed March 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb308fdcc8190b33da42f16cd65dd completed March 7, 2026, 11:21 p.m.
NEDg Description generation batch_69acb3a1978c819081cdc85f8fe10dd3 completed March 7, 2026, 11:24 p.m.
NED2 Entity disambiguation (via description) batch_69acb4132dbc8190b3e6c4880c33b7f2 completed March 7, 2026, 11:26 p.m.
Created at: March 1, 2026, 7:51 p.m.