Triple
T1683231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massachusetts Department of Correction |
E36382
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
MADOC
MADOC is the state agency responsible for overseeing and managing the prison and correctional system in Massachusetts.
|
E189327
|
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: MADOC | Statement: [Massachusetts Department of Correction, abbreviation, MADOC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MADOC Context triple: [Massachusetts Department of Correction, abbreviation, MADOC]
-
A.
MAD
MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
-
B.
MDOA
MDOA is the state agency responsible for advocating for and providing services to older adults and their caregivers in Maryland.
-
C.
MDW
MDW is the IATA airport code for Chicago Midway International Airport, a major commercial airport serving the Chicago metropolitan area in Illinois, USA.
-
D.
DOCO
DOCO is a mixed-use entertainment, shopping, and dining district in downtown Sacramento, California, adjacent to the Golden 1 Center.
-
E.
MFA Library
The MFA Library is the research and reference library of the Museum of Fine Arts, Boston, supporting scholarship on the museum’s collections, art history, and related fields.
- 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: MADOC Triple: [Massachusetts Department of Correction, abbreviation, MADOC]
Generated description
MADOC is the state agency responsible for overseeing and managing the prison and correctional system in Massachusetts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MADOC Target entity description: MADOC is the state agency responsible for overseeing and managing the prison and correctional system in Massachusetts.
-
A.
MAD
MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
-
B.
MDOA
MDOA is the state agency responsible for advocating for and providing services to older adults and their caregivers in Maryland.
-
C.
MDW
MDW is the IATA airport code for Chicago Midway International Airport, a major commercial airport serving the Chicago metropolitan area in Illinois, USA.
-
D.
DOCO
DOCO is a mixed-use entertainment, shopping, and dining district in downtown Sacramento, California, adjacent to the Golden 1 Center.
-
E.
MFA Library
The MFA Library is the research and reference library of the Museum of Fine Arts, Boston, supporting scholarship on the museum’s collections, art history, and related fields.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa627ab38081909d5f264ca49e036a |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad71bf1998819094d3eb67c6e6bafd |
completed | March 8, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_69ad7298ee288190b5e2b7d2ccb17a91 |
completed | March 8, 2026, 12:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad7305c7b48190a8a443dbc20ec9b2 |
completed | March 8, 2026, 1 p.m. |
Created at: March 4, 2026, 7:29 p.m.