Triple
T2047398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian Naval Component |
E45484
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
MCC
MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
|
E228212
|
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: MCC | Statement: [Belgian Naval Component, abbreviation, MCC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MCC Context triple: [Belgian Naval Component, abbreviation, MCC]
-
A.
MCA
MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
-
B.
MCA
MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
-
C.
MCG
MCG is a world-famous sports stadium in Melbourne, Australia, renowned as a premier venue for cricket and Australian rules football and for hosting major international sporting events.
-
D.
MCO
MCO is the National Rail station code used to identify Oxford Road railway station in Manchester, England.
-
E.
MCO
MCO is the IATA airport code for Orlando International Airport, a major air travel hub serving the Orlando, Florida metropolitan area and its tourist attractions.
- 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: MCC Triple: [Belgian Naval Component, abbreviation, MCC]
Generated description
MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MCC Target entity description: MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
-
A.
MCA
MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
-
B.
MCA
MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
-
C.
MCG
MCG is a world-famous sports stadium in Melbourne, Australia, renowned as a premier venue for cricket and Australian rules football and for hosting major international sporting events.
-
D.
MCO
MCO is the National Rail station code used to identify Oxford Road railway station in Manchester, England.
-
E.
MCO
MCO is the IATA airport code for Orlando International Airport, a major air travel hub serving the Orlando, Florida metropolitan area and its tourist attractions.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb974e8488190887b840c2cb88b3a |
completed | March 7, 2026, 5:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae2003e9488190b54ff042c91d4a62 |
completed | March 9, 2026, 1:19 a.m. |
| NEDg | Description generation | batch_69ae209544d881909438630ca5970d84 |
completed | March 9, 2026, 1:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae210b7b888190a879effa9d1e6ac3 |
completed | March 9, 2026, 1:23 a.m. |
Created at: March 4, 2026, 7:39 p.m.