Triple
T2289798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burlesque |
E51475
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object |
Michael Kaplan
Michael Kaplan is a composer and musician known for creating the music for the film "Burlesque."
|
E252767
|
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: Michael Kaplan | Statement: [Burlesque, musicBy, Michael Kaplan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Kaplan Context triple: [Burlesque, musicBy, Michael Kaplan]
-
A.
David Levien
David Levien is an American screenwriter, novelist, and producer best known for co-writing crime and heist films as well as co-creating the television series "Billions."
-
B.
Dan Goldberg
Dan Goldberg is a film producer best known for his work on major Hollywood comedies, including the hit movie "The Hangover."
-
C.
Jonathan I. Schwartz
Jonathan I. Schwartz is an American technology executive best known for serving as the CEO of Sun Microsystems during the mid-2000s.
-
D.
Jonathan Schwartz
Jonathan Schwartz is a film producer best known for his work on acclaimed independent movies such as "Like Crazy."
-
E.
Andrew G. Myers
Andrew G. Myers is an American organic chemist renowned for his contributions to complex molecule synthesis and medicinal chemistry.
- 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: Michael Kaplan Triple: [Burlesque, musicBy, Michael Kaplan]
Generated description
Michael Kaplan is a composer and musician known for creating the music for the film "Burlesque."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Kaplan Target entity description: Michael Kaplan is a composer and musician known for creating the music for the film "Burlesque."
-
A.
David Levien
David Levien is an American screenwriter, novelist, and producer best known for co-writing crime and heist films as well as co-creating the television series "Billions."
-
B.
Dan Goldberg
Dan Goldberg is a film producer best known for his work on major Hollywood comedies, including the hit movie "The Hangover."
-
C.
Jonathan I. Schwartz
Jonathan I. Schwartz is an American technology executive best known for serving as the CEO of Sun Microsystems during the mid-2000s.
-
D.
Jonathan Schwartz
Jonathan Schwartz is a film producer best known for his work on acclaimed independent movies such as "Like Crazy."
-
E.
Andrew G. Myers
Andrew G. Myers is an American organic chemist renowned for his contributions to complex molecule synthesis and medicinal chemistry.
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc273b67c8190bcd96f9a484647ef |
completed | March 7, 2026, 6:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f1e84ac819096cb62ce5e94d865 |
completed | March 9, 2026, 8:04 a.m. |
| NEDg | Description generation | batch_69ae7fee12ac8190bb9924f7467434a6 |
completed | March 9, 2026, 8:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae8061cd348190b0b0b65dcf730f99 |
completed | March 9, 2026, 8:10 a.m. |
Created at: March 4, 2026, 7:48 p.m.