Triple
T12589397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Buckley |
E300560
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object |
Mirabella
Mirabella is a fashion and lifestyle magazine known for its focus on sophisticated style and culture.
|
E993309
|
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: Mirabella | Statement: [Richard Buckley, employer, Mirabella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mirabella Context triple: [Richard Buckley, employer, Mirabella]
-
A.
Amorina
Amorina is a 19th-century Swedish novel by Carl Jonas Love Almqvist, known for its romantic and psychological depth within early modern Swedish literature.
-
B.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
-
C.
Belladère
Belladère is a commune and border town in central Haiti, located near the frontier with the Dominican Republic.
-
D.
Nerissa
Nerissa is a witty and loyal lady-in-waiting to Portia in Shakespeare’s play "The Merchant of Venice," known for her intelligence, humor, and role in the play’s romantic subplots.
-
E.
Laira
Laira is a suburb of Plymouth in Devon, England, situated along the River Plym and known for its residential areas and transport links.
- 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: Mirabella Triple: [Richard Buckley, employer, Mirabella]
Generated description
Mirabella is a fashion and lifestyle magazine known for its focus on sophisticated style and culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mirabella Target entity description: Mirabella is a fashion and lifestyle magazine known for its focus on sophisticated style and culture.
-
A.
Amorina
Amorina is a 19th-century Swedish novel by Carl Jonas Love Almqvist, known for its romantic and psychological depth within early modern Swedish literature.
-
B.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
-
C.
Belladère
Belladère is a commune and border town in central Haiti, located near the frontier with the Dominican Republic.
-
D.
Nerissa
Nerissa is a witty and loyal lady-in-waiting to Portia in Shakespeare’s play "The Merchant of Venice," known for her intelligence, humor, and role in the play’s romantic subplots.
-
E.
Laira
Laira is a suburb of Plymouth in Devon, England, situated along the River Plym and known for its residential areas and transport links.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954bd5e8c8190a2f233b91682341f |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ec0a60c8190948706e8b2fcc0ad |
completed | May 2, 2026, 8:29 p.m. |
| NEDg | Description generation | batch_69f662cc2a208190870e2099a8bb5d04 |
completed | May 2, 2026, 8:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6638319d48190ba73480ce6e91d83 |
completed | May 2, 2026, 8:50 p.m. |
Created at: April 9, 2026, 5:06 p.m.