Triple
T984641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Get Happy |
E21251
|
entity |
| Predicate | lyricist |
P1360
|
FINISHED |
| Object |
Ted Koehler
Ted Koehler was an American lyricist best known for his popular songs of the 1920s–1940s, many written in collaboration with composer Harold Arlen.
|
E142740
|
NE FINISHED |
How this triple was built (4 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: [Get Happy, lyricist, Ted Koehler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Koehler Context triple: [Get Happy, lyricist, Ted Koehler]
-
A.
Jeff Weltman
Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
-
B.
Joe Schoen
Joe Schoen is an American football executive best known as the general manager who helped lead the New York Giants’ recent roster rebuild and organizational turnaround.
-
C.
Kevin Yagher
Kevin Yagher is an American special effects and makeup artist and director best known for his work on horror and fantasy films and for creating iconic genre characters.
-
D.
Charles Begole
Charles Begole was an American mountaineer best known as one of the first climbers to reach the summit of Mount Whitney in the 19th century.
-
E.
Jack Briggs
Jack Briggs was an American actor best known for his marriage to Hollywood star Ginger Rogers.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ted Koehler Triple: [Get Happy, lyricist, Ted Koehler]
Generated description
Ted Koehler was an American lyricist best known for his popular songs of the 1920s–1940s, many written in collaboration with composer Harold Arlen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ted Koehler Target entity description: Ted Koehler was an American lyricist best known for his popular songs of the 1920s–1940s, many written in collaboration with composer Harold Arlen.
-
A.
Jeff Weltman
Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
-
B.
Joe Schoen
Joe Schoen is an American football executive best known as the general manager who helped lead the New York Giants’ recent roster rebuild and organizational turnaround.
-
C.
Kevin Yagher
Kevin Yagher is an American special effects and makeup artist and director best known for his work on horror and fantasy films and for creating iconic genre characters.
-
D.
Charles Begole
Charles Begole was an American mountaineer best known as one of the first climbers to reach the summit of Mount Whitney in the 19th century.
-
E.
Jack Briggs
Jack Briggs was an American actor best known for his marriage to Hollywood star Ginger Rogers.
- F. None of above. chosen
Provenance (5 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8f64ead48190be6f40e62b17bc12 |
completed | March 7, 2026, 8:49 p.m. |
| NEDg | Description generation | batch_69ac903eb12c8190a4024a71f15b19a4 |
completed | March 7, 2026, 8:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac916522b081908401b89261f99d50 |
completed | March 7, 2026, 8:58 p.m. |
Created at: March 1, 2026, 7:41 p.m.