Triple
T14623993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Hope You're Happy |
E343297
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Let Forever Mean Forever
"Let Forever Mean Forever" is a song featured on the album *I Hope You're Happy* by Blue October.
|
E1110452
|
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: Let Forever Mean Forever | Statement: [I Hope You're Happy, hasTrack, Let Forever Mean Forever]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Let Forever Mean Forever Context triple: [I Hope You're Happy, hasTrack, Let Forever Mean Forever]
-
A.
See Forever
See Forever is the promotional slogan used by One World Observatory to evoke its expansive, panoramic views over New York City and beyond.
-
B.
Now and Forever
"Now and Forever" is a romantic ballad by Carole King, best known as one of her later signature songs featured on her live album *The Living Room Tour*.
-
C.
Now & Forever
"Now & Forever" is a track by Canadian rapper Drake from his 2015 commercial mixtape *If You’re Reading This It’s Too Late*.
-
D.
How Forever Feels
"How Forever Feels" is a popular late-1990s country song by Kenny Chesney that became one of his early signature hits.
-
E.
Last Forever
"Last Forever" is the two-part series finale of the American sitcom How I Met Your Mother, known for its controversial conclusion to the long-running story.
- 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: Let Forever Mean Forever Triple: [I Hope You're Happy, hasTrack, Let Forever Mean Forever]
Generated description
"Let Forever Mean Forever" is a song featured on the album *I Hope You're Happy* by Blue October.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Let Forever Mean Forever Target entity description: "Let Forever Mean Forever" is a song featured on the album *I Hope You're Happy* by Blue October.
-
A.
See Forever
See Forever is the promotional slogan used by One World Observatory to evoke its expansive, panoramic views over New York City and beyond.
-
B.
Now and Forever
"Now and Forever" is a romantic ballad by Carole King, best known as one of her later signature songs featured on her live album *The Living Room Tour*.
-
C.
Now & Forever
"Now & Forever" is a track by Canadian rapper Drake from his 2015 commercial mixtape *If You’re Reading This It’s Too Late*.
-
D.
How Forever Feels
"How Forever Feels" is a popular late-1990s country song by Kenny Chesney that became one of his early signature hits.
-
E.
Last Forever
"Last Forever" is the two-part series finale of the American sitcom How I Met Your Mother, known for its controversial conclusion to the long-running story.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb468acc4819083b7e818d5cec809 |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda9288e748190bf65a01803265a73 |
completed | May 8, 2026, 9:13 a.m. |
| NEDg | Description generation | batch_69fdb27c8db481909330d299faded4f3 |
completed | May 8, 2026, 9:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdb3b24320819098dd7fab0c3a0507 |
completed | May 8, 2026, 9:58 a.m. |
Created at: April 10, 2026, 1:26 a.m.