Triple
T16096026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Each Dawn I Die |
E390486
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Heinz Roemheld |
E467716
|
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: Heinz Roemheld | Statement: [Each Dawn I Die, musicBy, Heinz Roemheld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heinz Roemheld Context triple: [Each Dawn I Die, musicBy, Heinz Roemheld]
-
A.
Heinz Roemheld
chosen
Heinz Roemheld was an American composer and pianist best known for his prolific work scoring Hollywood films during the 1930s and 1940s.
-
B.
Hans-Jürgen von Cramon-Taubadel
Hans-Jürgen von Cramon-Taubadel was a German Luftwaffe officer and fighter wing commander during World War II.
-
C.
Geert W. Schmid-Schönbein
Geert W. Schmid-Schönbein is a biomedical engineer and physiologist known for his research on microcirculation, inflammation, and the biomechanics of the cardiovascular system.
-
D.
Dr. Peter Lüttmann
Dr. Peter Lüttmann is a German local politician who serves as the mayor of the city of Rheine in North Rhine-Westphalia.
-
E.
Gerhard Kallmann
Gerhard Kallmann was a German-born American architect best known for co-designing the Brutalist-style Boston City Hall.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e18593d0fc8190aa3ba3edb4219aaa |
completed | April 17, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb991ba88190ad568a49069f9701 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 4:59 a.m.