Triple
T15264274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geth |
E364858
|
entity |
| Predicate | commandLineInterface |
P1594
|
FINISHED |
| Object |
geth
geth is the official Go implementation of an Ethereum node, providing a command-line client for running, managing, and interacting with the Ethereum blockchain.
|
E1147440
|
NE FINISHED |
How this triple was built (4 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: geth | Statement: [Geth, commandLineInterface, geth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: geth Context triple: [Geth, commandLineInterface, geth]
-
A.
BESU
BESU is a renowned engineering and science university in West Bengal, India, known for its strong technical education and research legacy.
-
B.
Besu
Besu is an open-source Java-based Ethereum client designed for enterprise and public network use, supporting both mainnet and private/permissioned blockchain deployments.
-
C.
Ropsten
Ropsten is an area and transport hub in northeastern Stockholm, Sweden, known as a gateway to the island of Lidingö.
-
D.
Gascoine
Gascoine is a surname most notably associated with English actress and novelist Jill Gascoine.
-
E.
Teku
Teku is an open-source Ethereum consensus client written in Java, designed to run Ethereum proof-of-stake validators in a secure and enterprise-friendly way.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: geth Triple: [Geth, commandLineInterface, geth]
Generated description
geth is the official Go implementation of an Ethereum node, providing a command-line client for running, managing, and interacting with the Ethereum blockchain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: geth Target entity description: geth is the official Go implementation of an Ethereum node, providing a command-line client for running, managing, and interacting with the Ethereum blockchain.
-
A.
BESU
BESU is a renowned engineering and science university in West Bengal, India, known for its strong technical education and research legacy.
-
B.
Besu
Besu is an open-source Java-based Ethereum client designed for enterprise and public network use, supporting both mainnet and private/permissioned blockchain deployments.
-
C.
Ropsten
Ropsten is an area and transport hub in northeastern Stockholm, Sweden, known as a gateway to the island of Lidingö.
-
D.
Gascoine
Gascoine is a surname most notably associated with English actress and novelist Jill Gascoine.
-
E.
Teku
Teku is an open-source Ethereum consensus client written in Java, designed to run Ethereum proof-of-stake validators in a secure and enterprise-friendly way.
- F. None of above. chosen
Provenance (5 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_69fee5fdc21881909d87062db6fb8fb7 |
completed | May 9, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69fee714cf6c81908dc4427590eeae85 |
completed | May 9, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feeae4731081909964bd8b1ea3dd7a |
completed | May 9, 2026, 8:05 a.m. |
Created at: April 10, 2026, 3:14 a.m.