Triple
T17260708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lifeblood |
E419000
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
I Live to Fall Asleep
"I Live to Fall Asleep" is a song by the Welsh rock band Funeral for a Friend from their album "Lifeblood."
|
E1259378
|
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: I Live to Fall Asleep | Statement: [Lifeblood, hasPart, I Live to Fall Asleep]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I Live to Fall Asleep Context triple: [Lifeblood, hasPart, I Live to Fall Asleep]
-
A.
Before I Sleep
Before I Sleep is an independent drama film centered on an aging poet reflecting on his life and regrets.
-
B.
Sleeping Where I Fall
Sleeping Where I Fall is Peter Coyote’s memoir recounting his experiences in the 1960s counterculture and his life as an activist, actor, and member of the San Francisco Diggers.
-
C.
I Don’t Sleep
"I Don’t Sleep" is a track by the American rapper Lil Wayne from his album "Funeral."
-
D.
Asleep in the Back
Asleep in the Back is the debut studio album by English rock band Elbow, known for its atmospheric sound and critically acclaimed songwriting.
-
E.
Light Sleeper
Light Sleeper is a 1992 neo-noir drama film written and directed by Paul Schrader, following a drug courier in New York City undergoing a moral and existential crisis.
- 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: I Live to Fall Asleep Triple: [Lifeblood, hasPart, I Live to Fall Asleep]
Generated description
"I Live to Fall Asleep" is a song by the Welsh rock band Funeral for a Friend from their album "Lifeblood."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: I Live to Fall Asleep Target entity description: "I Live to Fall Asleep" is a song by the Welsh rock band Funeral for a Friend from their album "Lifeblood."
-
A.
Before I Sleep
Before I Sleep is an independent drama film centered on an aging poet reflecting on his life and regrets.
-
B.
Sleeping Where I Fall
Sleeping Where I Fall is Peter Coyote’s memoir recounting his experiences in the 1960s counterculture and his life as an activist, actor, and member of the San Francisco Diggers.
-
C.
I Don’t Sleep
"I Don’t Sleep" is a track by the American rapper Lil Wayne from his album "Funeral."
-
D.
Asleep in the Back
Asleep in the Back is the debut studio album by English rock band Elbow, known for its atmospheric sound and critically acclaimed songwriting.
-
E.
Light Sleeper
Light Sleeper is a 1992 neo-noir drama film written and directed by Paul Schrader, following a drug courier in New York City undergoing a moral and existential crisis.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e70b00c8190b0380be08afae18d |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a017101d5dc8190ac6507344897b0f3 |
completed | May 11, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a0174d0014881908b99546055f9a781 |
completed | May 11, 2026, 6:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01758edf5c8190be0cfb3f7ba88796 |
completed | May 11, 2026, 6:22 a.m. |
Created at: April 10, 2026, 5:39 a.m.