Triple
T3972297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rise Against |
E92361
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object |
Ready to Fall
"Ready to Fall" is a politically charged punk rock song by Rise Against that addresses environmental destruction and humanity’s impact on the planet.
|
E405151
|
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: Ready to Fall | Statement: [Rise Against, notableSong, Ready to Fall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ready to Fall Context triple: [Rise Against, notableSong, Ready to Fall]
-
A.
Fallin’ Up
"Fallin’ Up" is a song by the Black Eyed Peas from their debut studio album, *Behind the Front*.
-
B.
Since We Fell
Since We Fell is a psychological thriller novel by Dennis Lehane that follows a former journalist whose life unravels after a public breakdown and the discovery of dark secrets about her seemingly perfect husband.
-
C.
Fell for You
"Fell for You" is a pop-punk song by Green Day from their 2012 album ¡Uno!.
-
D.
Fall in Love
"Fall in Love" is a popular Afrobeat love song by Nigerian artist D'banj that became one of his signature hits across Africa.
-
E.
Love Is Where It Falls
Love Is Where It Falls is a memoir by British actor and director Simon Callow reflecting on his intense, complex relationship with theatrical agent Peggy Ramsay.
- 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: Ready to Fall Triple: [Rise Against, notableSong, Ready to Fall]
Generated description
"Ready to Fall" is a politically charged punk rock song by Rise Against that addresses environmental destruction and humanity’s impact on the planet.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ready to Fall Target entity description: "Ready to Fall" is a politically charged punk rock song by Rise Against that addresses environmental destruction and humanity’s impact on the planet.
-
A.
Fallin’ Up
"Fallin’ Up" is a song by the Black Eyed Peas from their debut studio album, *Behind the Front*.
-
B.
Since We Fell
Since We Fell is a psychological thriller novel by Dennis Lehane that follows a former journalist whose life unravels after a public breakdown and the discovery of dark secrets about her seemingly perfect husband.
-
C.
Fell for You
"Fell for You" is a pop-punk song by Green Day from their 2012 album ¡Uno!.
-
D.
Fall in Love
"Fall in Love" is a popular Afrobeat love song by Nigerian artist D'banj that became one of his signature hits across Africa.
-
E.
Love Is Where It Falls
Love Is Where It Falls is a memoir by British actor and director Simon Callow reflecting on his intense, complex relationship with theatrical agent Peggy Ramsay.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef996ff6c8190ba8cc490e4744b95 |
completed | March 9, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5400fa9ac8190adf70a4c49eac32c |
completed | March 14, 2026, 11:01 a.m. |
| NEDg | Description generation | batch_69b5442537488190a7a99e09ee154057 |
completed | March 14, 2026, 11:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b544f60e288190973aaf0a4136a072 |
completed | March 14, 2026, 11:22 a.m. |
Created at: March 9, 2026, 3:32 p.m.