Triple
T22444034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LoopBack |
E554821
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | StrongLoop |
—
|
NE NERFINISHED |
How this triple was built (2 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: StrongLoop | Statement: [LoopBack, developer, StrongLoop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: StrongLoop Context triple: [LoopBack, developer, StrongLoop]
-
A.
StrongLoop
chosen
StrongLoop is a software company best known for its work on Node.js tools and frameworks, including previously maintaining the popular Express.js web application framework.
-
B.
LoopBack
LoopBack is an open-source Node.js framework for building APIs and connecting them to backend data sources.
-
C.
Knox Platform for Enterprise
Knox Platform for Enterprise is Samsung’s advanced mobile security and management solution designed to protect and control enterprise devices, apps, and data.
-
D.
MongoDB Realm
MongoDB Realm is a backend-as-a-service platform from MongoDB that provides real-time data synchronization, serverless functions, and application services tightly integrated with the MongoDB database.
-
E.
Actian
Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae517208190924a7968723f55ef |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.