Triple
T15264042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vyper |
E364852
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object | Solidity |
E364851
|
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: Solidity | Statement: [Vyper, competesWith, Solidity]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Solidity Context triple: [Vyper, competesWith, Solidity]
-
A.
Solidity
chosen
Solidity is a statically-typed, contract-oriented programming language primarily used to write and deploy smart contracts on the Ethereum platform and compatible blockchains.
-
B.
Vyper
Vyper is a Pythonic, security-focused programming language used to write smart contracts on the Ethereum blockchain.
-
C.
Ethereum Virtual Machine
The Ethereum Virtual Machine is a decentralized, sandboxed runtime that executes smart contracts and enforces the rules of the Ethereum blockchain across a global network of nodes.
-
D.
ETH
ETH is a leading Swiss public research university in Zurich renowned for its excellence in science, engineering, and technology.
-
E.
ETH
ETH is the ICAO airline designator used to identify Ethiopian Airlines in international aviation operations.
- 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_69e0084fed0481908e452c89cba2be82 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef6fc290819096ef03f8ecae8876 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:14 a.m.