Triple
T12530902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Between the Devil and the Deep Blue Sea |
E299559
|
entity |
| Predicate | hasLyricsBy |
P1141
|
FINISHED |
| Object | Ted Koehler |
E142740
|
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: Ted Koehler | Statement: [Between the Devil and the Deep Blue Sea, hasLyricsBy, Ted Koehler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Koehler Context triple: [Between the Devil and the Deep Blue Sea, hasLyricsBy, Ted Koehler]
-
A.
Ted Koehler
chosen
Ted Koehler was an American lyricist best known for his popular songs of the 1920s–1940s, many written in collaboration with composer Harold Arlen.
-
B.
Mark Kohr
Mark Kohr is an American music video director known for his work with prominent alternative rock bands in the 1990s.
-
C.
Ted Kaehler
Ted Kaehler is a computer scientist best known for his work on the Smalltalk programming language and object-oriented programming environments at Xerox PARC.
-
D.
Jack Kehler
Jack Kehler was an American character actor known for his quirky supporting roles in films and television, including appearances in works like The Big Lebowski and Men in Black II.
-
E.
Stephen Koepp
Stephen Koepp is an American journalist and editor best known as a longtime senior editor at Time magazine and co-founder of the business news site "From Day One."
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95469d100819087c83bc55e3ec9ce |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c6a590881908b0fe779f3698ea2 |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 8, 2026, 9:57 p.m.