Triple
T9534329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ministry of Education of Cuba |
E229973
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
MINED
MINED is the official acronym for Cuba’s Ministry of Education, the government body responsible for overseeing the national education system.
|
E806067
|
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: MINED | Statement: [Ministry of Education of Cuba, hasAbbreviation, MINED]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MINED Context triple: [Ministry of Education of Cuba, hasAbbreviation, MINED]
-
A.
Minning
Minning was the personal name of the Daoguang Emperor, a Qing dynasty ruler of China in the early to mid-19th century.
-
B.
Mined-Out
Mined-Out is an early 1983 ZX Spectrum puzzle video game by Ian Andrew that pioneered the grid-based mine-clearing gameplay later popularized by Minesweeper.
-
C.
Mines
Mines is a family surname shared by individuals such as William W. Mines.
-
D.
Mine
"Mine" is a country-pop song by Taylor Swift that opens her 2010 album *Speak Now* with a narrative about young love and emotional vulnerability.
-
E.
Miners
Miners is the nickname for the University of Texas at El Paso’s athletic teams, most prominently its NCAA Division I football program.
- 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: MINED Triple: [Ministry of Education of Cuba, hasAbbreviation, MINED]
Generated description
MINED is the official acronym for Cuba’s Ministry of Education, the government body responsible for overseeing the national education system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MINED Target entity description: MINED is the official acronym for Cuba’s Ministry of Education, the government body responsible for overseeing the national education system.
-
A.
Minning
Minning was the personal name of the Daoguang Emperor, a Qing dynasty ruler of China in the early to mid-19th century.
-
B.
Mined-Out
Mined-Out is an early 1983 ZX Spectrum puzzle video game by Ian Andrew that pioneered the grid-based mine-clearing gameplay later popularized by Minesweeper.
-
C.
Mines
Mines is a family surname shared by individuals such as William W. Mines.
-
D.
Mine
"Mine" is a country-pop song by Taylor Swift that opens her 2010 album *Speak Now* with a narrative about young love and emotional vulnerability.
-
E.
Miners
Miners is the nickname for the University of Texas at El Paso’s athletic teams, most prominently its NCAA Division I football program.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98cc58bc8190ba921410e4b64aaa |
completed | April 1, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c4804988190b99343734b4882e0 |
completed | April 4, 2026, 5:37 p.m. |
| NEDg | Description generation | batch_69d14e5455848190a0b2aa4d93204c6a |
completed | April 4, 2026, 5:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d14eab4b6c819081e1f54cc79bf49f |
completed | April 4, 2026, 5:47 p.m. |
Created at: March 30, 2026, 8 p.m.