Triple
T364254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Google Brain |
E7923
|
entity |
| Predicate | productDeveloped |
P490
|
FINISHED |
| Object | Google Neural Machine Translation system |
E13763
|
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: Google Neural Machine Translation system | Statement: [Google Brain, productDeveloped, Google Neural Machine Translation system]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Google Neural Machine Translation system Context triple: [Google Brain, productDeveloped, Google Neural Machine Translation system]
-
A.
Google Brain
Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
-
B.
Google Translate
chosen
Google Translate is a multilingual neural machine translation service by Google that instantly converts text, speech, images, and web pages between numerous languages.
-
C.
DeepMind
DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
-
D.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
-
E.
GPT-2
GPT-2 is a large transformer-based language model known for generating coherent, human-like text and sparking widespread discussion about the implications of advanced AI text generation.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ee29ede0819095279af95b53e350 |
completed | Feb. 28, 2026, 1:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3e86533a481909bab5f0b52114c6a |
completed | March 1, 2026, 7:19 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.