Triple
T1636153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM Db2 |
E35363
|
entity |
| Predicate | supportsStandard |
P1587
|
FINISHED |
| Object | ANSI SQL |
E5275
|
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: ANSI SQL | Statement: [IBM Db2, supportsStandard, ANSI SQL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ANSI SQL Context triple: [IBM Db2, supportsStandard, ANSI SQL]
-
A.
SQL
chosen
SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
-
B.
PL/SQL
PL/SQL is Oracle's proprietary procedural extension to SQL, used for writing stored procedures, functions, and complex database logic within Oracle Database.
-
C.
ANSI
ANSI is a private non-profit organization that oversees the development and coordination of voluntary consensus standards for products, services, processes, and systems in the United States.
-
D.
SQL Server
SQL Server is Microsoft's enterprise-grade relational database management system used for storing, managing, and analyzing data in a wide range of applications.
-
E.
JDBC
JDBC (Java Database Connectivity) is a Java-based API that enables applications to connect to and interact with relational databases in a standardized way.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a17e8e08190afb78a953ab920ec |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58dbd0608190be207ab2bcdc9eef |
completed | March 8, 2026, 11:09 a.m. |
Created at: March 4, 2026, 7:28 p.m.