Triple
T14455629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coco Before Chanel |
E358451
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Camille Fontaine
Camille Fontaine is a French screenwriter known for her work on acclaimed films such as "Coco Before Chanel."
|
E1100701
|
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: Camille Fontaine | Statement: [Coco Before Chanel, screenwriter, Camille Fontaine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camille Fontaine Context triple: [Coco Before Chanel, screenwriter, Camille Fontaine]
-
A.
Camille Henry
Camille Henry was a skilled Canadian ice hockey center best known for his prolific scoring with the New York Rangers in the 1950s and 1960s.
-
B.
Camille Roux
Camille Roux was an artist associated with the Impressionist movement who participated in the historic Impressionist exhibitions in late 19th-century France.
-
C.
Camille
Camille is a French given name used for both males and females, historically associated with figures such as the revolutionary journalist Camille Desmoulins.
-
D.
Camille
Camille is a character in Tennessee Williams’ play "Camino Real," a dreamlike drama set in a surreal, decaying town.
-
E.
Camille
Camille is a classic 1936 romantic drama film starring Greta Garbo as a tragic Parisian courtesan.
- 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: Camille Fontaine Triple: [Coco Before Chanel, screenwriter, Camille Fontaine]
Generated description
Camille Fontaine is a French screenwriter known for her work on acclaimed films such as "Coco Before Chanel."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Camille Fontaine Target entity description: Camille Fontaine is a French screenwriter known for her work on acclaimed films such as "Coco Before Chanel."
-
A.
Camille Henry
Camille Henry was a skilled Canadian ice hockey center best known for his prolific scoring with the New York Rangers in the 1950s and 1960s.
-
B.
Camille Roux
Camille Roux was an artist associated with the Impressionist movement who participated in the historic Impressionist exhibitions in late 19th-century France.
-
C.
Camille
Camille is a French given name used for both males and females, historically associated with figures such as the revolutionary journalist Camille Desmoulins.
-
D.
Camille
Camille is a character in Tennessee Williams’ play "Camino Real," a dreamlike drama set in a surreal, decaying town.
-
E.
Camille
Camille is a classic 1936 romantic drama film starring Greta Garbo as a tragic Parisian courtesan.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91a9c0d48190ae015e5e0db806ca |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd649177108190be32af72dcae04ee |
completed | May 8, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_69fd664347c48190a411141398794b88 |
completed | May 8, 2026, 4:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd66e5d6b08190ad94a6a5f1809c2a |
completed | May 8, 2026, 4:30 a.m. |
Created at: April 10, 2026, 1:19 a.m.