Triple

T8093953
Position Surface form Disambiguated ID Type / Status
Subject Apache Flink E188935 entity
Predicate hasAPI P182 FINISHED
Object SQL API
SQL API is a query interface in Apache Flink that lets users define streaming and batch data processing logic using standard SQL syntax.
 E711834 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: SQL API | Statement: [Apache Flink, hasAPI, SQL API]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SQL API
Context triple: [Apache Flink, hasAPI, SQL API]
  • A. SQL
    SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
  • B. DB
    DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
  • C. DB
    DB is the standard abbreviation for "Deutsche Biographie," a major German biographical reference work documenting notable figures from German history and culture.
  • D. SQLite
    SQLite is a lightweight, self-contained, serverless SQL database engine widely embedded in applications, operating systems, and devices.
  • E. ODBC
    ODBC (Open Database Connectivity) is a standard API that enables applications to access and query data from a wide variety of relational and non-relational database management systems using a common interface.
  • 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: SQL API
Triple: [Apache Flink, hasAPI, SQL API]
Generated description
SQL API is a query interface in Apache Flink that lets users define streaming and batch data processing logic using standard SQL syntax.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SQL API
Target entity description: SQL API is a query interface in Apache Flink that lets users define streaming and batch data processing logic using standard SQL syntax.
  • A. SQL
    SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
  • B. DB
    DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
  • C. DB
    DB is the standard abbreviation for "Deutsche Biographie," a major German biographical reference work documenting notable figures from German history and culture.
  • D. SQLite
    SQLite is a lightweight, self-contained, serverless SQL database engine widely embedded in applications, operating systems, and devices.
  • E. ODBC
    ODBC (Open Database Connectivity) is a standard API that enables applications to access and query data from a wide variety of relational and non-relational database management systems using a common interface.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb429089cc81909e4625f9cc7e305f completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc64112138819096050975d707d8ee completed April 1, 2026, 12:17 a.m.
NEDg Description generation batch_69cc68647cec81909736383fbe73d2e8 completed April 1, 2026, 12:35 a.m.
NED2 Entity disambiguation (via description) batch_69cc69b93bbc8190be2338182dd57b17 completed April 1, 2026, 12:41 a.m.
Created at: March 30, 2026, 5:30 p.m.