Triple
T2310638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Overground |
E51947
|
entity |
| Predicate | safetySystem |
P840
|
FINISHED |
| Object | AWS |
E86255
|
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: AWS | Statement: [London Overground, safetySystem, AWS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AWS Context triple: [London Overground, safetySystem, AWS]
-
A.
AWS
chosen
AWS is a train protection and warning system used on railways to alert drivers to signal aspects and speed restrictions, enhancing operational safety.
-
B.
Aws
Aws was one of the major Arab tribes of Medina that played a pivotal role in supporting Prophet Muhammad and the early Muslim community after the Hijrah.
-
C.
Amazon Web Services
Amazon Web Services is a leading global cloud computing platform offering on-demand infrastructure, storage, and application services to businesses, developers, and institutions.
-
D.
Azure
Azure is Microsoft's cloud computing platform offering a wide range of services for building, deploying, and managing applications and infrastructure through Microsoft-managed data centers.
-
E.
Amazon S3
Amazon S3 is a scalable, highly durable cloud object storage service from Amazon Web Services used for storing and retrieving large amounts of data over the internet.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc6098ce88190ba2e987e6f0737ac |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae8959d860819095ea3113e3d9264e |
completed | March 9, 2026, 8:48 a.m. |
Created at: March 4, 2026, 7:49 p.m.