Triple
T15744672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gemini SC-4 |
E381690
|
entity |
| Predicate | followedBy |
P78
|
FINISHED |
| Object | Gemini SC-5 |
E381690
|
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: Gemini SC-5 | Statement: [Gemini SC-4, followedBy, Gemini SC-5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gemini SC-5 Context triple: [Gemini SC-4, followedBy, Gemini SC-5]
-
A.
Gemini SC-4
chosen
Gemini SC-4 was the NASA spacecraft used for the Gemini 4 mission, which carried astronauts James McDivitt and Edward White on the first American spacewalk in 1965.
-
B.
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.
-
C.
Gemini Ultra
Gemini Ultra is Google’s most powerful large multimodal AI model in the Gemini family, designed for complex reasoning and advanced language and code tasks.
-
D.
Gemini 1.5
Gemini 1.5 is an advanced version of Google’s Gemini AI model family, offering improved multimodal reasoning and performance over earlier releases.
-
E.
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.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0502c0c3c8190b8e512df307039c1 |
completed | April 16, 2026, 2:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff876b7fd081909d84ebe7a4cdb675 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:46 a.m.