Triple
T10365967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cause Celeb |
E244250
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Oliver Marchant
Oliver Marchant is a central character in Helen Fielding’s novel "Cause Celeb," involved in the world of celebrity and humanitarian aid.
|
E857398
|
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: Oliver Marchant | Statement: [Cause Celeb, featuresCharacter, Oliver Marchant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oliver Marchant Context triple: [Cause Celeb, featuresCharacter, Oliver Marchant]
-
A.
Oliver Butcher
Oliver Butcher is a screenwriter known for co-writing films such as the thriller "Message from the King."
-
B.
Oliver Hubbard
Oliver Hubbard is an individual notable enough to be recognized as a prominent bearer of the surname Hubbard.
-
C.
Oliver Coppard
Oliver Coppard is a British Labour politician serving as the Mayor of South Yorkshire.
-
D.
Oliver Lambert
Oliver Lambert is the protagonist of the legal thriller "The Firm," around whom the story’s central conflicts and developments revolve.
-
E.
Oliver Heywood
Oliver Heywood was a prominent 19th-century Manchester banker and philanthropist known for his extensive charitable work and support of education and public institutions in the city.
- 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: Oliver Marchant Triple: [Cause Celeb, featuresCharacter, Oliver Marchant]
Generated description
Oliver Marchant is a central character in Helen Fielding’s novel "Cause Celeb," involved in the world of celebrity and humanitarian aid.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oliver Marchant Target entity description: Oliver Marchant is a central character in Helen Fielding’s novel "Cause Celeb," involved in the world of celebrity and humanitarian aid.
-
A.
Oliver Butcher
Oliver Butcher is a screenwriter known for co-writing films such as the thriller "Message from the King."
-
B.
Oliver Hubbard
Oliver Hubbard is an individual notable enough to be recognized as a prominent bearer of the surname Hubbard.
-
C.
Oliver Coppard
Oliver Coppard is a British Labour politician serving as the Mayor of South Yorkshire.
-
D.
Oliver Lambert
Oliver Lambert is the protagonist of the legal thriller "The Firm," around whom the story’s central conflicts and developments revolve.
-
E.
Oliver Heywood
Oliver Heywood was a prominent 19th-century Manchester banker and philanthropist known for his extensive charitable work and support of education and public institutions in the city.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e96f25f48190a41c8b0206b9238c |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d750c8c7588190a31bac5b774155fe |
completed | April 9, 2026, 7:10 a.m. |
| NEDg | Description generation | batch_69d751ab890c8190b1549619049dab91 |
completed | April 9, 2026, 7:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7619e97588190a1443f9438c6efc0 |
completed | April 9, 2026, 8:21 a.m. |
Created at: April 6, 2026, noon