Triple
T681412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Air Maroc |
E13189
|
entity |
| Predicate | ICAOCode |
P419
|
FINISHED |
| Object |
RAM
RAM is the ICAO airline designator used to identify Royal Air Maroc in international aviation operations and communications.
|
E82367
|
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: RAM | Statement: [Royal Air Maroc, ICAOCode, RAM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RAM Context triple: [Royal Air Maroc, ICAOCode, RAM]
-
A.
Mem
Mem is the thirteenth letter of the Hebrew alphabet, representing the "m" sound and having both standard and final written forms.
-
B.
DMA
DMA (Direct Memory Access) is a computer feature that allows hardware devices to transfer data directly to and from system memory without continuous CPU involvement, improving performance and efficiency.
-
C.
Monolithic Memories
Monolithic Memories was a semiconductor company known for developing programmable read-only memory (PROM) and logic devices after being spun off from Fairchild Semiconductor.
-
D.
RM
RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
-
E.
MMU
MMU is a large public university in Manchester, England, known for its diverse academic programs and strong links with industry and the creative sectors.
- 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: RAM Triple: [Royal Air Maroc, ICAOCode, RAM]
Generated description
RAM is the ICAO airline designator used to identify Royal Air Maroc in international aviation operations and communications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RAM Target entity description: RAM is the ICAO airline designator used to identify Royal Air Maroc in international aviation operations and communications.
-
A.
Mem
Mem is the thirteenth letter of the Hebrew alphabet, representing the "m" sound and having both standard and final written forms.
-
B.
DMA
DMA (Direct Memory Access) is a computer feature that allows hardware devices to transfer data directly to and from system memory without continuous CPU involvement, improving performance and efficiency.
-
C.
Monolithic Memories
Monolithic Memories was a semiconductor company known for developing programmable read-only memory (PROM) and logic devices after being spun off from Fairchild Semiconductor.
-
D.
RM
RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
-
E.
MMU
MMU is a large public university in Manchester, England, known for its diverse academic programs and strong links with industry and the creative sectors.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a06e294c8190873116a3253e04f9 |
completed | March 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5c3a5701c8190810e5e52bc2b61f7 |
completed | March 2, 2026, 5:06 p.m. |
| NEDg | Description generation | batch_69a5cd8acc888190b9bb80198bce5d00 |
completed | March 2, 2026, 5:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5ce6232e08190a8dba769f173f431 |
completed | March 2, 2026, 5:52 p.m. |
Created at: March 1, 2026, 7:36 p.m.