Triple
T9213752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tod Nielsen |
E221190
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Heroku |
E255524
|
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: Heroku | Statement: [Tod Nielsen, employer, Heroku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heroku Context triple: [Tod Nielsen, employer, Heroku]
-
A.
Heroku
chosen
Heroku is a cloud platform as a service (PaaS) that enables developers to build, run, and scale applications without managing underlying infrastructure.
-
B.
Vercel
Vercel is a cloud platform for frontend developers, best known for hosting and developing modern web applications and for creating the popular React framework Next.js.
-
C.
DigitalOcean
DigitalOcean is a cloud infrastructure provider known for its simple, developer-friendly platform offering virtual servers, storage, and networking services.
-
D.
Cloud9
Cloud9 is a prominent North American esports organization best known for its success across games like League of Legends, Counter-Strike, and Valorant.
-
E.
Cloud Foundry
Cloud Foundry is an open-source, multi-cloud application platform-as-a-service (PaaS) that automates the deployment, scaling, and management of cloud-native applications.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda06bf80819094c6e74b4b6a31e4 |
completed | April 1, 2026, 8:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d06613daf88190a0128fd53ea1b134 |
completed | April 4, 2026, 1:15 a.m. |
Created at: March 30, 2026, 7:27 p.m.