Triple
T20106532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gemini 2.0 |
E490192
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | Gemini 1.5 |
—
|
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: Gemini 1.5 | Statement: [Gemini 2.0, follows, Gemini 1.5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gemini 1.5 Context triple: [Gemini 2.0, follows, Gemini 1.5]
-
A.
Gemini 1.5
chosen
Gemini 1.5 is an advanced version of Google’s Gemini AI model family, offering improved multimodal reasoning and performance over earlier releases.
-
B.
Gemini 1.0
Gemini 1.0 is an early version of Google's multimodal large language model that preceded the more advanced Gemini 1.5.
-
C.
Gemini 2.0
Gemini 2.0 is a major updated release of Google’s multimodal AI model family, designed to provide more powerful and versatile capabilities across text, code, image, and other modalities.
-
D.
Gemini Pro
Gemini Pro is a powerful large language model in Google’s Gemini family designed for advanced reasoning, coding, and multimodal AI tasks.
-
E.
Gemini Nano
Gemini Nano is a lightweight, on-device variant of Google’s Gemini AI model designed to run efficiently on mobile and edge devices.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666dcb8d4819091889e19dd9137a6 |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:28 p.m.