Triple
T18204234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RoBERTa |
E435864
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Facebook AI |
—
|
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: Facebook AI | Statement: [RoBERTa, developer, Facebook AI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Facebook AI Context triple: [RoBERTa, developer, Facebook AI]
-
A.
Meta AI
chosen
Meta AI is Meta Platforms’ artificial intelligence division, responsible for developing large-scale AI models, research, and consumer-facing tools like the Meta AI assistant integrated across its apps and services.
-
B.
Facebook Engineering
Facebook Engineering is the division of Meta responsible for developing and maintaining Facebook’s core software infrastructure, products, and internal technologies.
-
C.
Meta Platforms data center
The Meta Platforms data center is a large-scale computing facility operated by Meta (formerly Facebook) to support its social media, messaging, and virtual reality services.
-
D.
Google Brain
Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
-
E.
Apple AI/ML organization
Apple AI/ML organization is Apple’s internal division focused on advancing artificial intelligence and machine learning research and integrating these technologies into the company’s products and services.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e221bbbc819088a7559a46b7d4e7 |
completed | April 19, 2026, 2:09 p.m. |
Created at: April 10, 2026, 10:32 a.m.