Triple

T23110888
Position Surface form Disambiguated ID Type / Status
Subject Linhas Aéreas de Moçambique E576315 entity
Predicate ICAOcode P419 FINISHED
Object LAM
LAM is the ICAO airline designator for Linhas Aéreas de Moçambique, the national flag carrier of Mozambique.
 E1571354 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: LAM | Statement: [Linhas Aéreas de Moçambique, ICAOcode, LAM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LAM
Context triple: [Linhas Aéreas de Moçambique, ICAOcode, LAM]
  • A. Lam
    Lam is a shortened form of the name Lambert, commonly used as a nickname or informal variant.
  • B. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • C. LMA
    LMA is a comprehensive system for observing, describing, and interpreting human movement developed from the work of choreographer and movement theorist Rudolf Laban.
  • D. LMA
    LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
  • E. LAMA
    LAMA is a light utility helicopter model, derived from the Aérospatiale SA 315 Lama, known for its high-altitude performance and use in mountain rescue and transport operations.
  • 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: LAM
Triple: [Linhas Aéreas de Moçambique, ICAOcode, LAM]
Generated description
LAM is the ICAO airline designator for Linhas Aéreas de Moçambique, the national flag carrier of Mozambique.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LAM
Target entity description: LAM is the ICAO airline designator for Linhas Aéreas de Moçambique, the national flag carrier of Mozambique.
  • A. Lam
    Lam is a shortened form of the name Lambert, commonly used as a nickname or informal variant.
  • B. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • C. LMA
    LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
  • D. LMA
    LMA is a comprehensive system for observing, describing, and interpreting human movement developed from the work of choreographer and movement theorist Rudolf Laban.
  • E. LAMA
    LAMA is a light utility helicopter model, derived from the Aérospatiale SA 315 Lama, known for its high-altitude performance and use in mountain rescue and transport operations.
  • 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_69e245f4af548190898d434a64a1e774 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e0f4d188190a9395074c630ab0d completed April 29, 2026, 4:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c23ea3e908190baf83cd72e23bbb7 completed May 19, 2026, 8:48 a.m.
NEDg Description generation batch_6a0c28ed782c8190a60cf2212a1e7861 completed May 19, 2026, 9:10 a.m.
NED2 Entity disambiguation (via description) batch_6a0c29bca4c08190a29d4204c75b333f completed May 19, 2026, 9:13 a.m.
Created at: April 17, 2026, 3:58 p.m.