Triple
T7388030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyclone |
E170429
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object | Lattice ECP family |
E656346
|
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: Lattice ECP family | Statement: [Cyclone, competesWith, Lattice ECP family]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lattice ECP family Context triple: [Cyclone, competesWith, Lattice ECP family]
-
A.
Koblitz curves
Koblitz curves are a special class of elliptic curves defined over binary fields that enable particularly efficient and fast implementations of elliptic curve cryptography.
-
B.
Lattice ECP5
chosen
Lattice ECP5 is a family of low-power, mid-range FPGAs designed for cost-sensitive, high-volume applications such as communications, industrial, and consumer electronics.
-
C.
ECC
ECC is a public-key cryptography approach that uses the mathematics of elliptic curves to provide strong security with relatively small key sizes.
-
D.
ECC
ECC is the National Rail station code for Eccles railway station in Greater Manchester, England.
-
E.
ECC
The ECC is Pakistan’s top economic decision-making body, responsible for key fiscal and economic policy approvals within the federal government.
- 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_69c68a5e2c9081909e713ce866e0060a |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1f3f5f48190aabe69ba79cbcb93 |
completed | March 27, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802e56fb48190976612d2a94d6ee5 |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:09 p.m.