Triple
T12562602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sybase |
E295385
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Sybase IQ |
E295385
|
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: Sybase IQ | Statement: [Sybase, product, Sybase IQ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sybase IQ Context triple: [Sybase, product, Sybase IQ]
-
A.
Sybase
chosen
Sybase is a pioneering enterprise software company best known for its relational database management systems and data management solutions, later acquired by SAP.
-
B.
SAP MaxDB
SAP MaxDB is a relational database management system developed by SAP, commonly used for enterprise applications and SAP solutions.
-
C.
Teradata
Teradata is an enterprise-grade relational database management system and data warehousing platform designed for large-scale analytics and business intelligence workloads.
-
D.
IBM Netezza Performance Server
IBM Netezza Performance Server is a high-performance, cloud-ready data warehouse and analytics platform designed for fast, large-scale data processing and advanced analytics workloads.
-
E.
Actian
Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95494ae1c81908b9ee14b8ef92a65 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6558da7e0819086860bfaf394e2d8 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:48 p.m.