Triple
T148079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python |
E3372
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object |
Ruby
Ruby is a dynamic, object-oriented programming language known for its elegant syntax and its use in the Ruby on Rails web framework.
|
E17647
|
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: Ruby | Statement: [Python, influenced, Ruby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruby Context triple: [Python, influenced, Ruby]
-
A.
Python
Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
-
B.
Java
Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
-
C.
Java
Java is a widely used, object-oriented programming language known for its platform independence and extensive use in enterprise, web, and mobile application development.
-
D.
Ada (programming language)
Ada is a statically typed, high-level programming language designed with strong support for reliability, safety, and real-time systems, widely used in mission-critical and embedded applications such as aerospace and defense.
-
E.
JavaScript
JavaScript is a high-level, dynamic programming language primarily used to create interactive and dynamic content on web pages.
- 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: Ruby Triple: [Python, influenced, Ruby]
Generated description
Ruby is a dynamic, object-oriented programming language known for its elegant syntax and its use in the Ruby on Rails web framework.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ruby Target entity description: Ruby is a dynamic, object-oriented programming language known for its elegant syntax and its use in the Ruby on Rails web framework.
-
A.
Python
Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
-
B.
Java
Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
-
C.
Java
Java is a widely used, object-oriented programming language known for its platform independence and extensive use in enterprise, web, and mobile application development.
-
D.
Ada (programming language)
Ada is a statically typed, high-level programming language designed with strong support for reliability, safety, and real-time systems, widely used in mission-critical and embedded applications such as aerospace and defense.
-
E.
JavaScript
JavaScript is a high-level, dynamic programming language primarily used to create interactive and dynamic content on web pages.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a257ecb6f48190992c4c8ca908a81c |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2c27754a881908ef5a96e05e515e3 |
completed | Feb. 28, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69a2c37177348190857d52872e6ab393 |
completed | Feb. 28, 2026, 10:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2c3c512f08190bb87f874524b1616 |
completed | Feb. 28, 2026, 10:30 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.