Triple
T16436881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lovehunter |
E399200
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Mean Business
Mean Business is a song by the British hard rock band Whitesnake from their 1979 album "Lovehunter."
|
E1214152
|
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: Mean Business | Statement: [Lovehunter, hasPart, Mean Business]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mean Business Context triple: [Lovehunter, hasPart, Mean Business]
-
A.
The Business
The Business is a British television series featuring actress Caroline Harker in a prominent role.
-
B.
The Business
The Business is a satirical science fiction novel by Iain M. Banks that follows a powerful, secretive multinational corporation with quasi-governmental influence as seen through the eyes of one of its high-ranking executives.
-
C.
The Business
The Business is a film featuring actor Geoff Bell in a prominent role.
-
D.
It’s a Business
"It’s a Business" is a musical number from the Broadway show *Curtains*, characterized by its satirical take on the commercial side of show business.
-
E.
Mean
"Mean" is a country-pop song by Taylor Swift from her album "Speak Now," widely recognized for its anti-bullying message and empowering lyrics about overcoming criticism.
- 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: Mean Business Triple: [Lovehunter, hasPart, Mean Business]
Generated description
Mean Business is a song by the British hard rock band Whitesnake from their 1979 album "Lovehunter."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mean Business Target entity description: Mean Business is a song by the British hard rock band Whitesnake from their 1979 album "Lovehunter."
-
A.
The Business
The Business is a British television series featuring actress Caroline Harker in a prominent role.
-
B.
The Business
The Business is a satirical science fiction novel by Iain M. Banks that follows a powerful, secretive multinational corporation with quasi-governmental influence as seen through the eyes of one of its high-ranking executives.
-
C.
The Business
The Business is a film featuring actor Geoff Bell in a prominent role.
-
D.
It’s a Business
"It’s a Business" is a musical number from the Broadway show *Curtains*, characterized by its satirical take on the commercial side of show business.
-
E.
Mean
"Mean" is a country-pop song by Taylor Swift from her album "Speak Now," widely recognized for its anti-bullying message and empowering lyrics about overcoming criticism.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ba49f3481908e7ea62467ef5813 |
completed | April 18, 2026, 6:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0045893c5481909e5ffa9460dc5b3d |
completed | May 10, 2026, 8:44 a.m. |
| NEDg | Description generation | batch_6a0049a7079881909d6edc17aa80536c |
completed | May 10, 2026, 9:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a004aba97348190870f366bf9364761 |
completed | May 10, 2026, 9:07 a.m. |
Created at: April 10, 2026, 5:10 a.m.