Triple

T11148498
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Foreign Affairs of Latvia E263725 entity
Predicate hasAbbreviation P43 FINISHED
Object LR ĀM
LR ĀM is the official Latvian abbreviation for the country’s Ministry of Foreign Affairs.
 E906840 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: LR ĀM | Statement: [Ministry of Foreign Affairs of Latvia, hasAbbreviation, LR ĀM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LR ĀM
Context triple: [Ministry of Foreign Affairs of Latvia, hasAbbreviation, LR ĀM]
  • A. LR
    LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
  • B. LR
    LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
  • C. LR
    LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
  • D. LR
    LR is the commonly used abbreviation for Les Républicains, a major center-right political party in France.
  • E. LER
    LER is the vehicle registration code assigned to the German island municipality of Borkum.
  • 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: LR ĀM
Triple: [Ministry of Foreign Affairs of Latvia, hasAbbreviation, LR ĀM]
Generated description
LR ĀM is the official Latvian abbreviation for the country’s Ministry of Foreign Affairs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LR ĀM
Target entity description: LR ĀM is the official Latvian abbreviation for the country’s Ministry of Foreign Affairs.
  • A. LR
    LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
  • B. LR
    LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
  • C. LR
    LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
  • D. LR
    LR is the commonly used abbreviation for Les Républicains, a major center-right political party in France.
  • E. LER
    LER is the vehicle registration code assigned to the German island municipality of Borkum.
  • 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_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8701ea481908c86c2359f5dc957 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e442248e588190b59866c79169c43a completed April 19, 2026, 2:47 a.m.
NEDg Description generation batch_69e44c0a9edc8190a184244ba63f1c8f completed April 19, 2026, 3:29 a.m.
NED2 Entity disambiguation (via description) batch_69e4513731fc8190be0bae62d1e16e6f completed April 19, 2026, 3:51 a.m.
Created at: April 8, 2026, 9:28 p.m.