Triple
T14502015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Origin of Love |
E340164
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Make You Happy
"Make You Happy" is a song featured on the album *The Origin of Love* by French singer-songwriter Mika.
|
E1102605
|
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: Make You Happy | Statement: [The Origin of Love, hasPart, Make You Happy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Make You Happy Context triple: [The Origin of Love, hasPart, Make You Happy]
-
A.
Make You Happy
"Make You Happy" is a song featured on Céline Dion’s 1996 album *Falling into You*.
-
B.
You Are My Happy
"You Are My Happy" is a bestselling children's picture book by Hoda Kotb that celebrates the loving bond and everyday joys shared between a parent and child.
-
C.
Born to Make You Happy
"Born to Make You Happy" is a pop ballad by Britney Spears that became one of her early international hits, particularly in Europe.
-
D.
Make Someone Happy
"Make Someone Happy" is a jazz album by Russian-Canadian vocalist Sophie Milman, showcasing her interpretations of classic standards.
-
E.
Happy with You
"Happy with You" is a melodic, introspective song by Paul McCartney from his 2018 studio album "Egypt Station."
- 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: Make You Happy Triple: [The Origin of Love, hasPart, Make You Happy]
Generated description
"Make You Happy" is a song featured on the album *The Origin of Love* by French singer-songwriter Mika.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Make You Happy Target entity description: "Make You Happy" is a song featured on the album *The Origin of Love* by French singer-songwriter Mika.
-
A.
Make You Happy
"Make You Happy" is a song featured on Céline Dion’s 1996 album *Falling into You*.
-
B.
You Are My Happy
"You Are My Happy" is a bestselling children's picture book by Hoda Kotb that celebrates the loving bond and everyday joys shared between a parent and child.
-
C.
Born to Make You Happy
"Born to Make You Happy" is a pop ballad by Britney Spears that became one of her early international hits, particularly in Europe.
-
D.
Make Someone Happy
"Make Someone Happy" is a jazz album by Russian-Canadian vocalist Sophie Milman, showcasing her interpretations of classic standards.
-
E.
Happy with You
"Happy with You" is a melodic, introspective song by Paul McCartney from his 2018 studio album "Egypt Station."
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e0f9048190a2d266cfa4f9dfb6 |
completed | April 14, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d9b6f7481908b7eb76226a93545 |
completed | May 8, 2026, 4:59 a.m. |
| NEDg | Description generation | batch_69fd6efed3108190a524c64adf740303 |
completed | May 8, 2026, 5:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd6f8648408190aed910a7f269abee |
completed | May 8, 2026, 5:07 a.m. |
Created at: April 10, 2026, 1:21 a.m.