Triple
T9898122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ADO.NET |
E182224
|
entity |
| Predicate | coreClass |
P18973
|
FINISHED |
| Object |
DataRow
DataRow is a fundamental ADO.NET class that represents a single row of data within a DataTable, providing access to and manipulation of the row’s column values.
|
E827338
|
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: DataRow | Statement: [ADO.NET, coreClass, DataRow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DataRow Context triple: [ADO.NET, coreClass, DataRow]
-
A.
DataView
DataView is ML.NET’s core, schema-aware tabular data abstraction used to efficiently represent and process datasets for machine learning pipelines.
-
B.
DB Records
DB Records is a Nigerian music label founded by and associated with Afrobeats star D'banj.
-
C.
DSN
DSN is the acronym for NASA’s Deep Space Network, a global system of large radio antennas used to communicate with and track interplanetary spacecraft and distant space missions.
-
D.
DB
DB is the standard abbreviation for "Deutsche Biographie," a major German biographical reference work documenting notable figures from German history and culture.
-
E.
DB
DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
- 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: DataRow Triple: [ADO.NET, coreClass, DataRow]
Generated description
DataRow is a fundamental ADO.NET class that represents a single row of data within a DataTable, providing access to and manipulation of the row’s column values.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DataRow Target entity description: DataRow is a fundamental ADO.NET class that represents a single row of data within a DataTable, providing access to and manipulation of the row’s column values.
-
A.
DataView
DataView is ML.NET’s core, schema-aware tabular data abstraction used to efficiently represent and process datasets for machine learning pipelines.
-
B.
DB Records
DB Records is a Nigerian music label founded by and associated with Afrobeats star D'banj.
-
C.
DSN
DSN is the acronym for NASA’s Deep Space Network, a global system of large radio antennas used to communicate with and track interplanetary spacecraft and distant space missions.
-
D.
DB
DB is the standard abbreviation for "Deutsche Biographie," a major German biographical reference work documenting notable figures from German history and culture.
-
E.
DB
DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4ac27d88190b8255f7e616f95c9 |
completed | April 2, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb17ed548190a2510a667dd988ca |
completed | April 5, 2026, 4:54 a.m. |
| NEDg | Description generation | batch_69d1ebca75a08190a298e8fa322ebcfc |
completed | April 5, 2026, 4:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1ec19045c81909aa23c971454b3a5 |
completed | April 5, 2026, 4:59 a.m. |
Created at: March 30, 2026, 8:40 p.m.