Triple
T23979284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cora Corman |
E604460
|
entity |
| Predicate | notableSongInFilm |
P42255
|
FINISHED |
| Object |
Buddha’s Delight
"Buddha’s Delight" is a pop song best known for its prominent feature in the 2007 film "Music and Lyrics," where it is performed by the fictional teen pop star Cora Corman.
|
E1615097
|
NE FINISHED |
How this triple was built (3 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: Buddha’s Delight | Statement: [Cora Corman, notableSongInFilm, Buddha’s Delight]
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: Buddha’s Delight Triple: [Cora Corman, notableSongInFilm, Buddha’s Delight]
Generated description
"Buddha’s Delight" is a pop song best known for its prominent feature in the 2007 film "Music and Lyrics," where it is performed by the fictional teen pop star Cora Corman.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSongInFilm Context triple: [Cora Corman, notableSongInFilm, Buddha’s Delight]
-
A.
songFeaturedInFilm
chosen
Indicates that a particular song is included or used within a specific film.
-
B.
notableSongWrittenFor
Indicates that a particular song was specifically written for a given person, group, work, event, or purpose.
-
C.
notableSongInMusical
Indicates that a particular song is especially prominent, well-known, or significant within a given musical.
-
D.
notableSongAssociations
Indicates that there are notable or significant associations between an entity and specific songs, such as being referenced by, inspiring, or otherwise prominently linked to those songs.
-
E.
songRepopularizedByFilm
Indicates that a previously released song regained popularity as a result of being featured in a film.
- F. None of above.
Provenance (6 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_69e29543f40c819087700b7a272afb60 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d2bc79688190bc98a2d57b91f5a3 |
completed | April 29, 2026, 9:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0f7e8153d88190b4753be2df39f958 |
completed | May 21, 2026, 9:52 p.m. |
| NEDg | Description generation | batch_6a0f80e2f8c88190b04dcf47b416f934 |
completed | May 21, 2026, 10:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0f81d0818881908066cf3d819cb013 |
completed | May 21, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:26 p.m.