Triple
T14148816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maputo International Airport |
E350620
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
MPM
MPM is the IATA airport code for Maputo International Airport, the main international gateway to Maputo, Mozambique.
|
E1081718
|
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: MPM | Statement: [Maputo International Airport, IATAcode, MPM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MPM Context triple: [Maputo International Airport, IATAcode, MPM]
-
A.
MPM-10
MPM-10 is a modern rubber-tired metro train model used on the Montreal Metro, designed to increase capacity, comfort, and energy efficiency.
-
B.
MMP
MMP is a hybrid electoral system that combines single-member district representation with proportional party lists to align a legislature’s overall seat distribution with parties’ share of the vote.
-
C.
MMPS
MMPS is the ICAO airport code assigned to Puerto Escondido International Airport in Oaxaca, Mexico.
-
D.
MPS
MPS (Metal Performance Shaders) is an Apple framework that provides highly optimized GPU-accelerated compute and graphics shaders for tasks like image processing and machine learning on Apple devices.
-
E.
MPS
MPS is a language workbench and integrated development environment by JetBrains designed for creating and working with domain-specific languages using projectional editing.
- 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: MPM Triple: [Maputo International Airport, IATAcode, MPM]
Generated description
MPM is the IATA airport code for Maputo International Airport, the main international gateway to Maputo, Mozambique.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MPM Target entity description: MPM is the IATA airport code for Maputo International Airport, the main international gateway to Maputo, Mozambique.
-
A.
MPM-10
MPM-10 is a modern rubber-tired metro train model used on the Montreal Metro, designed to increase capacity, comfort, and energy efficiency.
-
B.
MMP
MMP is a hybrid electoral system that combines single-member district representation with proportional party lists to align a legislature’s overall seat distribution with parties’ share of the vote.
-
C.
MMPS
MMPS is the ICAO airport code assigned to Puerto Escondido International Airport in Oaxaca, Mexico.
-
D.
MPS
MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
-
E.
MPS
MPS is a language workbench and integrated development environment by JetBrains designed for creating and working with domain-specific languages using projectional editing.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61237ef481909374c1f68a2370b7 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf205c788190920b5055f9fe63a8 |
completed | May 7, 2026, 6:51 p.m. |
| NEDg | Description generation | batch_69fce266b2a08190998f04913064e43f |
completed | May 7, 2026, 7:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fce2cd8cb481908e3e5a421e732948 |
completed | May 7, 2026, 7:06 p.m. |
Created at: April 10, 2026, 12:55 a.m.