Triple
T34436335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Old Piano |
E883964
|
entity |
| Predicate | chartPositionBelgiumNote |
P185985
|
FINISHED |
| Object | peaked in the top 10 in Belgium |
—
|
LITERAL 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: peaked in the top 10 in Belgium | Statement: [My Old Piano, chartPositionBelgiumNote, peaked in the top 10 in Belgium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chartPositionBelgiumNote Context triple: [My Old Piano, chartPositionBelgiumNote, peaked in the top 10 in Belgium]
-
A.
chartPositionBelgiumFlanders
Indicates the position or ranking something holds on the music charts specifically in the Flanders region of Belgium.
-
B.
chartPositionBelgiumWallonia
Indicates the position or ranking of something on the music charts specifically in the Wallonia region of Belgium.
-
C.
positionInBelgium
Indicates that one entity occupies a specific geographic location within the territory of Belgium.
-
D.
chartPositionAustria
Indicates the position or ranking that something holds on a music or sales chart specifically in Austria.
-
E.
chartPositionEurope
Indicates the position or ranking of something on a music or sales chart specifically within European markets.
- F. None of above. chosen
Provenance (4 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_69f349c548d88190978e2a82502c03d0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7c83f5960819089610ed39c839678 |
completed | May 3, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
| PDg | Predicate description generation | batch_69f7c776b4088190bef550c869da530d |
completed | May 3, 2026, 10:08 p.m. |
Created at: May 1, 2026, 2 a.m.