Triple
T18856404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 24: The Game |
E461179
|
entity |
| Predicate | hasGameEngine |
P26587
|
FINISHED |
| Object | Kinetica |
—
|
NE NERFINISHED |
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: Kinetica | Statement: [24: The Game, hasGameEngine, Kinetica]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kinetica Context triple: [24: The Game, hasGameEngine, Kinetica]
-
A.
Kinetica
chosen
Kinetica is a proprietary game engine developed by Sony Computer Entertainment, known for powering several early PlayStation 2 titles.
-
B.
Vertica
Vertica is a high-performance, column-oriented analytical database system designed for large-scale data warehousing and real-time analytics.
-
C.
Actian
Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
-
D.
Greenplum
Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
-
E.
Ebixa
Ebixa is a brand-name medication containing memantine, used primarily to treat moderate to severe Alzheimer's disease.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c05d0bb8819094d0447441f85b57 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 10, 2026, 11:57 a.m.