Triple

T11015305
Position Surface form Disambiguated ID Type / Status
Subject Marsa Matruh International Airport E260348 entity
Predicate IATAcode P418 FINISHED
Object MUH
MUH is the IATA airport code for Marsa Matruh International Airport, which serves the coastal city of Mersa Matruh in Egypt.
 E900165 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: MUH | Statement: [Marsa Matruh International Airport, IATAcode, MUH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MUH
Context triple: [Marsa Matruh International Airport, IATAcode, MUH]
  • A. MUHBA
    MUHBA is Barcelona’s city history museum, dedicated to preserving and showcasing the urban, archaeological, and cultural heritage of Barcelona.
  • B. MUHA
    MUHA is the ICAO airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • C. MUF
    MUF is the youth wing of Sweden's Moderate Party, engaging young people in center-right politics and policy issues.
  • D. MU
    MU is the common abbreviation for Masaryk University, a major public research university located in Brno, Czech Republic.
  • E. MU
    MU is the IATA airline designator assigned to China Eastern Airlines, one of China’s major carriers.
  • 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: MUH
Triple: [Marsa Matruh International Airport, IATAcode, MUH]
Generated description
MUH is the IATA airport code for Marsa Matruh International Airport, which serves the coastal city of Mersa Matruh in Egypt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MUH
Target entity description: MUH is the IATA airport code for Marsa Matruh International Airport, which serves the coastal city of Mersa Matruh in Egypt.
  • A. MUHBA
    MUHBA is Barcelona’s city history museum, dedicated to preserving and showcasing the urban, archaeological, and cultural heritage of Barcelona.
  • B. MUHA
    MUHA is the ICAO airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • C. MUF
    MUF is the youth wing of Sweden's Moderate Party, engaging young people in center-right politics and policy issues.
  • D. MU
    MU is the common abbreviation for Masaryk University, a major public research university located in Brno, Czech Republic.
  • E. MU
    MU is the IATA airline designator assigned to China Eastern Airlines, one of China’s major carriers.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797a558a08190bdb5779faa9adf05 completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e374d371ec8190aba9e77346c6e876 completed April 18, 2026, 12:10 p.m.
NEDg Description generation batch_69e37ab6ca788190ac41f9494ad9a47f completed April 18, 2026, 12:36 p.m.
NED2 Entity disambiguation (via description) batch_69e37c9439fc8190a69cfb1a13da4c19 completed April 18, 2026, 12:44 p.m.
Created at: April 8, 2026, 9:25 p.m.