Triple
T931099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadcasting Board of Governors |
E20093
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
BBG
BBG is the former U.S. federal agency that oversaw government-funded international media outlets such as Voice of America and Radio Free Europe/Radio Liberty.
|
E109625
|
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: BBG | Statement: [Broadcasting Board of Governors, shortName, BBG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BBG Context triple: [Broadcasting Board of Governors, shortName, BBG]
-
A.
BnG
BnG is the commonly used abbreviation for Bòrd na Gàidhlig, the principal public body responsible for promoting and supporting the Scottish Gaelic language in Scotland.
-
B.
BG
BG is the two-letter ISO 3166-1 alpha-2 country code representing Bulgaria.
-
C.
LBG
LBG is the IATA airport code for Paris–Le Bourget Airport, a historic airfield near Paris known for hosting the Paris Air Show.
-
D.
BB-37
BB-37 is the hull number of USS Oklahoma, a Nevada-class battleship of the United States Navy that was sunk during the attack on Pearl Harbor in 1941.
-
E.
JBLU
JBLU is the stock ticker symbol for JetBlue Airways, a major U.S.-based low-cost airline.
- 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: BBG Triple: [Broadcasting Board of Governors, shortName, BBG]
Generated description
BBG is the former U.S. federal agency that oversaw government-funded international media outlets such as Voice of America and Radio Free Europe/Radio Liberty.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BBG Target entity description: BBG is the former U.S. federal agency that oversaw government-funded international media outlets such as Voice of America and Radio Free Europe/Radio Liberty.
-
A.
BnG
BnG is the commonly used abbreviation for Bòrd na Gàidhlig, the principal public body responsible for promoting and supporting the Scottish Gaelic language in Scotland.
-
B.
BG
BG is the two-letter ISO 3166-1 alpha-2 country code representing Bulgaria.
-
C.
LBG
LBG is the IATA airport code for Paris–Le Bourget Airport, a historic airfield near Paris known for hosting the Paris Air Show.
-
D.
BB-37
BB-37 is the hull number of USS Oklahoma, a Nevada-class battleship of the United States Navy that was sunk during the attack on Pearl Harbor in 1941.
-
E.
JBLU
JBLU is the stock ticker symbol for JetBlue Airways, a major U.S.-based low-cost airline.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b34b302c81908fa32cb18f551493 |
completed | March 1, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7ee1108188190a26c73864c697061 |
completed | March 4, 2026, 8:32 a.m. |
| NEDg | Description generation | batch_69a7f1a1214481909538745d5713e402 |
completed | March 4, 2026, 8:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7f2303534819094ae764b20d223ee |
completed | March 4, 2026, 8:49 a.m. |
Created at: March 1, 2026, 7:40 p.m.