Triple
T21247656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Greenburg |
E523655
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Love Kills
Love Kills is a crime novel by American author Dan Greenburg, known for its darkly comic and suspenseful exploration of murder and obsession.
|
E1472841
|
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: Love Kills | Statement: [Dan Greenburg, notableWork, Love Kills]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Kills Context triple: [Dan Greenburg, notableWork, Love Kills]
-
A.
Love Kills
"Love Kills" is a song by the Ramones from their 1986 album *Animal Boy*, inspired by the story of Sid Vicious and Nancy Spungen.
-
B.
Keep Her
"Keep Her" is a song by British-Irish girl group The Saturdays from their debut album "Chasing Lights."
-
C.
Beautiful Disaster
"Beautiful Disaster" is a pop ballad by American singer Kelly Clarkson that appears on her debut studio album, "Thankful."
-
D.
Beautiful Disaster
"Beautiful Disaster" is a popular alternative rock song by the band 311, known for its melodic blend of rock, reggae, and rap elements.
-
E.
Beautiful Disaster
"Beautiful Disaster" is a 2023 romantic drama film based on Jamie McGuire’s novel, following the tumultuous relationship between a college bad boy and a seemingly good girl.
- 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: Love Kills Triple: [Dan Greenburg, notableWork, Love Kills]
Generated description
Love Kills is a crime novel by American author Dan Greenburg, known for its darkly comic and suspenseful exploration of murder and obsession.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Love Kills Target entity description: Love Kills is a crime novel by American author Dan Greenburg, known for its darkly comic and suspenseful exploration of murder and obsession.
-
A.
Love Kills
"Love Kills" is a song by the Ramones from their 1986 album *Animal Boy*, inspired by the story of Sid Vicious and Nancy Spungen.
-
B.
Keep Her
"Keep Her" is a song by British-Irish girl group The Saturdays from their debut album "Chasing Lights."
-
C.
Beautiful Disaster
"Beautiful Disaster" is a popular alternative rock song by the band 311, known for its melodic blend of rock, reggae, and rap elements.
-
D.
Beautiful Disaster
"Beautiful Disaster" is a pop ballad by American singer Kelly Clarkson that appears on her debut studio album, "Thankful."
-
E.
Beautiful Disaster
"Beautiful Disaster" is a 2023 romantic drama film based on Jamie McGuire’s novel, following the tumultuous relationship between a college bad boy and a seemingly good girl.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359b756c819085480ca4174c53c2 |
completed | April 21, 2026, 8:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0986f8e32c8190b056d98a2627e417 |
completed | May 17, 2026, 9:14 a.m. |
| NEDg | Description generation | batch_6a0987b7bd548190bf3f026bbb49be3c |
completed | May 17, 2026, 9:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0988b4bbdc8190a7e08bb6558047fa |
completed | May 17, 2026, 9:21 a.m. |
Created at: April 16, 2026, 3:55 p.m.