Triple
T3663541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya-Maya Airport |
E77706
|
entity |
| Predicate | hasICAOcode |
P419
|
FINISHED |
| Object |
FCBB
FCBB is the ICAO airport code for Maya-Maya Airport, the main international airport serving Brazzaville in the Republic of the Congo.
|
E378654
|
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: FCBB | Statement: [Maya-Maya Airport, hasICAOcode, FCBB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FCBB Context triple: [Maya-Maya Airport, hasICAOcode, FCBB]
-
A.
BCB
BCB is the Central Bank of Brazil, the country’s primary monetary authority responsible for implementing monetary policy, regulating the financial system, and issuing currency.
-
B.
CCFC
CCFC is the commonly used abbreviation for Cardiff City Football Club, a professional football team based in Cardiff, Wales.
-
C.
FFC
FFC is the commonly used abbreviation for Falkirk Football Club, a professional Scottish football team based in Falkirk.
-
D.
FFC
FFC is the common abbreviation for Fluminense Football Club, a traditional Brazilian sports club best known for its professional football team based in Rio de Janeiro.
-
E.
FHLBB
FHLBB was the former U.S. federal agency that regulated and supervised the Federal Home Loan Bank System and savings and loan institutions.
- 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: FCBB Triple: [Maya-Maya Airport, hasICAOcode, FCBB]
Generated description
FCBB is the ICAO airport code for Maya-Maya Airport, the main international airport serving Brazzaville in the Republic of the Congo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FCBB Target entity description: FCBB is the ICAO airport code for Maya-Maya Airport, the main international airport serving Brazzaville in the Republic of the Congo.
-
A.
BCB
BCB is the Central Bank of Brazil, the country’s primary monetary authority responsible for implementing monetary policy, regulating the financial system, and issuing currency.
-
B.
CCFC
CCFC is the commonly used abbreviation for Cardiff City Football Club, a professional football team based in Cardiff, Wales.
-
C.
FFC
FFC is the commonly used abbreviation for Falkirk Football Club, a professional Scottish football team based in Falkirk.
-
D.
FFC
FFC is the common abbreviation for Fluminense Football Club, a traditional Brazilian sports club best known for its professional football team based in Rio de Janeiro.
-
E.
FHLBB
FHLBB was the former U.S. federal agency that regulated and supervised the Federal Home Loan Bank System and savings and loan institutions.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3fe5eb08190ab15044acf9ac8a9 |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48848be788190acde46880918d36b |
completed | March 13, 2026, 9:57 p.m. |
| NEDg | Description generation | batch_69b489c9a21081908b5e6468205e5c68 |
completed | March 13, 2026, 10:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4bcaa45cc8190a5db8bfd8845efb1 |
completed | March 14, 2026, 1:40 a.m. |
Created at: March 8, 2026, 3:25 p.m.