Triple
T12562599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sybase |
E295385
|
entity |
| Predicate | originalName |
P65
|
FINISHED |
| Object | Sybase, Inc. |
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, Inc. | Statement: [Sybase, originalName, Sybase, Inc.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sybase, Inc. Context triple: [Sybase, originalName, Sybase, Inc.]
-
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.
Actian
Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
-
C.
SAP MaxDB
SAP MaxDB is a relational database management system developed by SAP, commonly used for enterprise applications and SAP solutions.
-
D.
Relational Technology Inc.
Relational Technology Inc. was a pioneering software company best known for developing and marketing the INGRES relational database system, one of the early commercial SQL-based databases.
-
E.
Siebel Systems
Siebel Systems was a leading enterprise software company best known for pioneering customer relationship management (CRM) solutions for large organizations.
- 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.