Triple
T2351187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Macbeth |
E47451
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Nick Emerson
Nick Emerson is an editor known for his work on editions of Shakespearean plays, including "Lady Macbeth."
|
E257880
|
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: Nick Emerson | Statement: [Lady Macbeth, editedBy, Nick Emerson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nick Emerson Context triple: [Lady Macbeth, editedBy, Nick Emerson]
-
A.
Nick Swinmurn
Nick Swinmurn is an American entrepreneur best known for creating the online shoe and clothing retailer Zappos, which became a pioneering force in e-commerce and customer service.
-
B.
Marc Eversley
Marc Eversley is a Canadian basketball executive known for serving as the general manager of the NBA’s Chicago Bulls.
-
C.
Eric Pearson
Eric Pearson is an American screenwriter best known for his work on Marvel Cinematic Universe films, including writing the screenplay for "Thor: Ragnarok."
-
D.
Christopher Le Brun
Christopher Le Brun is a British painter, sculptor, and printmaker who served as President of the Royal Academy of Arts in London.
-
E.
Jonathan Evans
Jonathan Evans is a British politician and former Member of Parliament who has served in both the UK and European Parliaments.
- 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: Nick Emerson Triple: [Lady Macbeth, editedBy, Nick Emerson]
Generated description
Nick Emerson is an editor known for his work on editions of Shakespearean plays, including "Lady Macbeth."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nick Emerson Target entity description: Nick Emerson is an editor known for his work on editions of Shakespearean plays, including "Lady Macbeth."
-
A.
Nick Swinmurn
Nick Swinmurn is an American entrepreneur best known for creating the online shoe and clothing retailer Zappos, which became a pioneering force in e-commerce and customer service.
-
B.
Marc Eversley
Marc Eversley is a Canadian basketball executive known for serving as the general manager of the NBA’s Chicago Bulls.
-
C.
Eric Pearson
Eric Pearson is an American screenwriter best known for his work on Marvel Cinematic Universe films, including writing the screenplay for "Thor: Ragnarok."
-
D.
Christopher Le Brun
Christopher Le Brun is a British painter, sculptor, and printmaker who served as President of the Royal Academy of Arts in London.
-
E.
Jonathan Evans
Jonathan Evans is a British politician and former Member of Parliament who has served in both the UK and European Parliaments.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae962f769881909a7713880eaa9b84 |
completed | March 9, 2026, 9:43 a.m. |
| NEDg | Description generation | batch_69ae96b399608190bfa846c433612142 |
completed | March 9, 2026, 9:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae977e539c81909cef638cc61e5ec1 |
completed | March 9, 2026, 9:48 a.m. |
Created at: March 4, 2026, 7:54 p.m.