Triple
T15267352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cray XK7 |
E364932
|
entity |
| Predicate | marketedAs |
P1395
|
FINISHED |
| Object | Cray XK7 series |
E364932
|
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: Cray XK7 series | Statement: [Cray XK7, marketedAs, Cray XK7 series]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cray XK7 series Context triple: [Cray XK7, marketedAs, Cray XK7 series]
-
A.
Cray XK7
chosen
Cray XK7 is a high-performance supercomputer architecture developed by Cray Inc., notable for combining traditional CPUs with GPU accelerators to achieve petascale computing power.
-
B.
Cray XC30
The Cray XC30 is a high-performance supercomputer system designed for large-scale scientific and engineering computing, featuring advanced scalability and energy-efficient architecture.
-
C.
Cray XC50
The Cray XC50 is a high-performance supercomputer system designed for large-scale scientific and engineering computing workloads.
-
D.
Cray XC40
The Cray XC40 is a high-performance supercomputing system designed for large-scale scientific and engineering workloads in research and enterprise environments.
-
E.
Cray XE6
Cray XE6 is a high-performance supercomputing platform designed by Cray Inc. for massively parallel scientific and engineering applications.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0094ca9ac8190a1f97a7b74c96cd5 |
completed | April 15, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff755e0f2c819088293d8a55d7883a |
completed | May 9, 2026, 5:56 p.m. |
Created at: April 10, 2026, 3:14 a.m.