Triple
T19859323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let Love In |
E477214
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Loverman
"Loverman" is a dark, brooding song by Nick Cave and the Bad Seeds, known for its menacing atmosphere and intense vocal delivery.
|
E1398263
|
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: Loverman | Statement: [Let Love In, hasTrack, Loverman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loverman Context triple: [Let Love In, hasTrack, Loverman]
-
A.
Mr Loverman
Mr Loverman is a critically acclaimed novel by Bernardine Evaristo that explores the life, sexuality, and hidden desires of an elderly Antiguan-British man in London.
-
B.
Lover Alot
Lover Alot is a hard-rock track by Aerosmith featured on their 2012 studio album "Music from Another Dimension!".
-
C.
Demonlover
Demonlover is a 2002 French neo-noir thriller film that explores corporate espionage, digital pornography, and globalization through a cold, disorienting narrative style.
-
D.
Lovergirl
"Lovergirl" is a popular 1984 R&B and funk single by American singer Teena Marie, known for its catchy groove and powerful vocals.
-
E.
Lovere
Lovere is a picturesque historic town in northern Italy, known for its scenic position on the shores of Lake Iseo and its medieval and Renaissance architecture.
- 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: Loverman Triple: [Let Love In, hasTrack, Loverman]
Generated description
"Loverman" is a dark, brooding song by Nick Cave and the Bad Seeds, known for its menacing atmosphere and intense vocal delivery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Loverman Target entity description: "Loverman" is a dark, brooding song by Nick Cave and the Bad Seeds, known for its menacing atmosphere and intense vocal delivery.
-
A.
Mr Loverman
Mr Loverman is a critically acclaimed novel by Bernardine Evaristo that explores the life, sexuality, and hidden desires of an elderly Antiguan-British man in London.
-
B.
Lover Alot
Lover Alot is a hard-rock track by Aerosmith featured on their 2012 studio album "Music from Another Dimension!".
-
C.
Demonlover
Demonlover is a 2002 French neo-noir thriller film that explores corporate espionage, digital pornography, and globalization through a cold, disorienting narrative style.
-
D.
Lovergirl
"Lovergirl" is a popular 1984 R&B and funk single by American singer Teena Marie, known for its catchy groove and powerful vocals.
-
E.
Lovere
Lovere is a picturesque historic town in northern Italy, known for its scenic position on the shores of Lake Iseo and its medieval and Renaissance architecture.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6586e8b648190bb650d7f2816dda1 |
completed | April 20, 2026, 4:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07d447708081908f18b105491af0c4 |
completed | May 16, 2026, 2:19 a.m. |
| NEDg | Description generation | batch_6a07d50359f08190bafa8865168ee0b4 |
completed | May 16, 2026, 2:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d5d7c4bc8190ab189fa556a956d7 |
completed | May 16, 2026, 2:26 a.m. |
Created at: April 10, 2026, 1:51 p.m.