Triple
T18148875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In the Air Tonight |
E434454
|
entity |
| Predicate | chartedIn |
P19348
|
FINISHED |
| Object | German Singles Chart |
—
|
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: German Singles Chart | Statement: [In the Air Tonight, chartedIn, German Singles Chart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: German Singles Chart Context triple: [In the Air Tonight, chartedIn, German Singles Chart]
-
A.
German Singles Chart
chosen
The German Singles Chart is the official weekly ranking of the most popular singles in Germany, based on sales and streaming data.
-
B.
Dutch Singles Chart
The Dutch Singles Chart is a national music ranking in the Netherlands that lists the most popular singles based on sales, streaming, and airplay.
-
C.
Swiss Singles Chart
The Swiss Singles Chart is Switzerland’s official ranking of the most popular singles, typically based on sales and streaming data.
-
D.
Swedish Singles Chart
The Swedish Singles Chart is Sweden's official ranking of the most popular singles, typically based on sales and streaming data.
-
E.
European Hot 100
The European Hot 100 was a pan-European music singles chart that ranked the most popular songs across numerous European countries.
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de372e8081908b52fe33c870716e |
completed | April 19, 2026, 1:52 p.m. |
Created at: April 10, 2026, 10:29 a.m.