Triple
T5382010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 陳士駿 |
E113105
|
entity |
| Predicate | coFounded |
P104
|
FINISHED |
| Object | AVOS Systems |
E107971
|
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: AVOS Systems | Statement: [陳士駿, coFounded, AVOS Systems]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AVOS Systems Context triple: [陳士駿, coFounded, AVOS Systems]
-
A.
AVOS Systems
chosen
AVOS Systems was a technology company co-founded by YouTube’s creators that focused on developing and managing online consumer web services and social bookmarking platforms.
-
B.
Nentego
Nentego is the autonym of the Nanticoke people, an Indigenous group historically located in the Mid-Atlantic region of what is now the United States.
-
C.
MongoDB Inc.
MongoDB Inc. is a software company best known for developing the popular open-source NoSQL document database MongoDB, widely used for scalable, modern application development.
-
D.
Actian
Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
-
E.
CloudKit
CloudKit is Apple’s cloud storage and data synchronization framework that enables developers to seamlessly store, manage, and sync app data across users’ iCloud accounts and devices.
- 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_69bd4436a1988190af18dcff7fd306b4 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd86d163f88190939638d44fcb24a7 |
completed | March 20, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf294cb9288190ab1400dae18332de |
completed | March 21, 2026, 11:27 p.m. |
Created at: March 20, 2026, 2:03 p.m.