Triple
T20036342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blueberry Yum Yum |
E497276
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | LVM |
—
|
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: LVM | Statement: [Blueberry Yum Yum, producer, LVM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LVM Context triple: [Blueberry Yum Yum, producer, LVM]
-
A.
LVM
LVM is the Finnish Ministry of Transport and Communications, the government body responsible for national transport infrastructure, communications policy, and related regulatory frameworks in Finland.
-
B.
LVM
chosen
LVM is a music producer known for working on tracks such as "Blow It Out."
-
C.
LVM3
LVM3 is India’s heavy-lift launch vehicle developed by ISRO to carry large communication and deep-space satellites into orbit.
-
D.
LVM-Thin
LVM-Thin is a Linux Logical Volume Manager feature that provides thin-provisioned storage pools, enabling efficient, flexible allocation of disk space for virtual machines and containers.
-
E.
Veritas Volume Manager (in some versions)
Veritas Volume Manager is a storage management software product that provides advanced logical volume management, including features like disk virtualization, mirroring, and dynamic resizing for enterprise environments.
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662e8573081909f71fda640aa3220 |
completed | April 20, 2026, 5:31 p.m. |
Created at: April 11, 2026, 3:36 p.m.