Triple
T12321997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AWS Lambda |
E293752
|
entity |
| Predicate | supportsTrigger |
P36418
|
FINISHED |
| Object | Amazon SQS |
E293769
|
NE FINISHED |
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: Amazon SQS | Statement: [AWS Lambda, supportsTrigger, Amazon SQS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazon SQS Context triple: [AWS Lambda, supportsTrigger, Amazon SQS]
-
A.
Amazon SQS
chosen
Amazon SQS is a fully managed message queuing service that enables decoupled, scalable communication between distributed application components in the cloud.
-
B.
Amazon MQ
Amazon MQ is a managed message broker service that simplifies setting up and operating popular open-source message brokers like Apache ActiveMQ and RabbitMQ in the cloud.
-
C.
Azure Service Bus
Azure Service Bus is a fully managed enterprise message broker on Microsoft Azure that enables reliable, asynchronous communication between distributed applications and services.
-
D.
Amazon Kinesis
Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
-
E.
Amazon SNS
Amazon SNS is a fully managed pub/sub messaging service that enables applications, microservices, and users to send and receive notifications at scale via multiple communication channels.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4d7dac81909ff10e64e229ef33 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e8aa94881908e4c184062037ab5 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:53 p.m.