Triple
T3506072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burgenland |
E74077
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Rust
Rust is a small historic town in Austria’s Burgenland region, renowned for its well-preserved medieval architecture and wine culture along Lake Neusiedl.
|
E363629
|
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: Rust | Statement: [Burgenland, hasTown, Rust]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rust Context triple: [Burgenland, hasTown, Rust]
-
A.
Rust
Rust is a modern systems programming language focused on memory safety, concurrency, and performance without a garbage collector.
-
B.
Rust Foundation
The Rust Foundation is a non-profit organization that supports the development, ecosystem, and community of the Rust programming language.
-
C.
Deno
Deno is a modern, secure JavaScript and TypeScript runtime created by Ryan Dahl as a successor to Node.js, featuring built-in TypeScript support and a permission-based security model.
-
D.
Elm
Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
-
E.
Elm
Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end applications.
- 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: Rust Triple: [Burgenland, hasTown, Rust]
Generated description
Rust is a small historic town in Austria’s Burgenland region, renowned for its well-preserved medieval architecture and wine culture along Lake Neusiedl.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rust Target entity description: Rust is a small historic town in Austria’s Burgenland region, renowned for its well-preserved medieval architecture and wine culture along Lake Neusiedl.
-
A.
Rust
Rust is a modern systems programming language focused on memory safety, concurrency, and performance without a garbage collector.
-
B.
Rust Foundation
The Rust Foundation is a non-profit organization that supports the development, ecosystem, and community of the Rust programming language.
-
C.
Deno
Deno is a modern, secure JavaScript and TypeScript runtime created by Ryan Dahl as a successor to Node.js, featuring built-in TypeScript support and a permission-based security model.
-
D.
Elm
Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
-
E.
Elm
Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end applications.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbf38e988190998d722b95830411 |
completed | March 8, 2026, 6:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373e0dc7881909af631182970d132 |
completed | March 13, 2026, 2:18 a.m. |
| NEDg | Description generation | batch_69b375337e6c8190a3d2a1561c133ecb |
completed | March 13, 2026, 2:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b375bb3f8c819097b295a2881b3b82 |
completed | March 13, 2026, 2:26 a.m. |
Created at: March 8, 2026, 3:18 p.m.