Triple
T15108338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MongoDB Inc. |
E360845
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object |
MongoDB Atlas Vector Search
MongoDB Atlas Vector Search is a managed, cloud-native vector search capability within MongoDB Atlas that enables building AI and semantic search applications by storing and querying vector embeddings alongside operational data.
|
E1138549
|
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: MongoDB Atlas Vector Search | Statement: [MongoDB Inc., product, MongoDB Atlas Vector Search]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MongoDB Atlas Vector Search Context triple: [MongoDB Inc., product, MongoDB Atlas Vector Search]
-
A.
MongoDB Cloud
MongoDB Cloud is a fully managed cloud database platform that provides scalable, secure, and globally distributed MongoDB database services along with tools for data management, monitoring, and analytics.
-
B.
MongoDB API
MongoDB API is a MongoDB-compatible interface that allows applications to interact with certain non-MongoDB databases (such as Azure Cosmos DB) using MongoDB drivers and query syntax.
-
C.
openCypher API
The openCypher API is a graph query interface based on the Cypher language, enabling developers to query and manipulate property graph data in systems like Amazon Neptune.
-
D.
Azure Cognitive Search
Azure Cognitive Search is a fully managed cloud search service from Microsoft that provides AI-powered indexing and querying capabilities over structured and unstructured data.
-
E.
MongoDB database
MongoDB database is a popular open-source NoSQL document-oriented database designed for scalability, flexibility, and high performance in modern applications.
- 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: MongoDB Atlas Vector Search Triple: [MongoDB Inc., product, MongoDB Atlas Vector Search]
Generated description
MongoDB Atlas Vector Search is a managed, cloud-native vector search capability within MongoDB Atlas that enables building AI and semantic search applications by storing and querying vector embeddings alongside operational data.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MongoDB Atlas Vector Search Target entity description: MongoDB Atlas Vector Search is a managed, cloud-native vector search capability within MongoDB Atlas that enables building AI and semantic search applications by storing and querying vector embeddings alongside operational data.
-
A.
MongoDB Cloud
MongoDB Cloud is a fully managed cloud database platform that provides scalable, secure, and globally distributed MongoDB database services along with tools for data management, monitoring, and analytics.
-
B.
MongoDB API
MongoDB API is a MongoDB-compatible interface that allows applications to interact with certain non-MongoDB databases (such as Azure Cosmos DB) using MongoDB drivers and query syntax.
-
C.
openCypher API
The openCypher API is a graph query interface based on the Cypher language, enabling developers to query and manipulate property graph data in systems like Amazon Neptune.
-
D.
Azure Cognitive Search
Azure Cognitive Search is a fully managed cloud search service from Microsoft that provides AI-powered indexing and querying capabilities over structured and unstructured data.
-
E.
MongoDB database
MongoDB database is a popular open-source NoSQL document-oriented database designed for scalability, flexibility, and high performance in modern applications.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058af8988190977d998f85893836 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7e912ac8190bd0e0c9cdbbd0194 |
completed | May 9, 2026, 4:28 a.m. |
| NEDg | Description generation | batch_69feba1d256c8190ba13379d0cb8135c |
completed | May 9, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feba93c4cc819083c683210d1f03f8 |
completed | May 9, 2026, 4:39 a.m. |
Created at: April 10, 2026, 3:05 a.m.