Triple
T20935276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandala Airlines |
E515567
|
entity |
| Predicate | ICAOCode |
P419
|
FINISHED |
| Object |
MDL
MDL is the ICAO airline designator assigned to Mandala Airlines, an Indonesian commercial carrier.
|
E1457585
|
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: MDL | Statement: [Mandala Airlines, ICAOCode, MDL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MDL Context triple: [Mandala Airlines, ICAOCode, MDL]
-
A.
MDL
MDL is the official currency code for the Moldovan leu, the national currency of Moldova.
-
B.
MDL
MDL is the IATA airport code for Mandalay International Airport, the main air gateway to Mandalay in Myanmar.
-
C.
MDL
MDL is the abbreviation commonly used for the Military Demarcation Line that separates North and South Korea along the Korean Demilitarized Zone.
-
D.
MDL
MDL (Material Definition Language) is NVIDIA’s high-level language for defining physically based materials and their appearance consistently across different rendering and simulation platforms.
-
E.
MDL
MDL is a major Indian state-owned shipbuilding company based in Mumbai, known for constructing warships and submarines for the Indian Navy.
- 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: MDL Triple: [Mandala Airlines, ICAOCode, MDL]
Generated description
MDL is the ICAO airline designator assigned to Mandala Airlines, an Indonesian commercial carrier.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MDL Target entity description: MDL is the ICAO airline designator assigned to Mandala Airlines, an Indonesian commercial carrier.
-
A.
MDL
MDL is the IATA airport code for Mandalay International Airport, the main air gateway to Mandalay in Myanmar.
-
B.
MDL
MDL is a major Indian state-owned shipbuilding company based in Mumbai, known for constructing warships and submarines for the Indian Navy.
-
C.
MDL
MDL is the official currency code for the Moldovan leu, the national currency of Moldova.
-
D.
MDL
MDL is a Lisp-derived programming language developed at MIT for advanced artificial intelligence research and interactive computing.
-
E.
MDL
MDL is the abbreviation commonly used for the Military Demarcation Line that separates North and South Korea along the Korean Demilitarized Zone.
- 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f950d5e081908ec0df4824cf69f7 |
completed | April 21, 2026, 4:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a091fd28890819091e20c282b0811ae |
completed | May 17, 2026, 1:54 a.m. |
| NEDg | Description generation | batch_6a09204848848190acdd189dc88990ed |
completed | May 17, 2026, 1:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0920c819a08190b040bb9e89309eb9 |
completed | May 17, 2026, 1:58 a.m. |
Created at: April 16, 2026, 12:49 p.m.