Triple
T18875365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaya DaCosta |
E461669
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Camara
Camara is the given name of American actress and model Yaya DaCosta, known for her work in film, television, and fashion.
|
E1347615
|
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: Camara | Statement: [Yaya DaCosta, givenName, Camara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camara Context triple: [Yaya DaCosta, givenName, Camara]
-
A.
Camira
Camira is a compact family car model produced by Holden, the Australian subsidiary of General Motors, during the 1980s.
-
B.
Camira
Camira is a residential suburb located within the Ipswich City Council area in South East Queensland, Australia.
-
C.
Caméra One
Caméra One is a French film production company known for producing acclaimed art-house and auteur-driven movies.
-
D.
The Camera
The Camera is a seminal photography book by Ansel Adams that explores the technical and artistic use of cameras in creating expressive photographs.
-
E.
Megacam
Megacam is a wide-field optical imaging camera used on large ground-based telescopes for deep, high-resolution astronomical surveys.
- 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: Camara Triple: [Yaya DaCosta, givenName, Camara]
Generated description
Camara is the given name of American actress and model Yaya DaCosta, known for her work in film, television, and fashion.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Camara Target entity description: Camara is the given name of American actress and model Yaya DaCosta, known for her work in film, television, and fashion.
-
A.
Camira
Camira is a compact family car model produced by Holden, the Australian subsidiary of General Motors, during the 1980s.
-
B.
Camira
Camira is a residential suburb located within the Ipswich City Council area in South East Queensland, Australia.
-
C.
Caméra One
Caméra One is a French film production company known for producing acclaimed art-house and auteur-driven movies.
-
D.
The Camera
The Camera is a seminal photography book by Ansel Adams that explores the technical and artistic use of cameras in creating expressive photographs.
-
E.
Megacam
Megacam is a wide-field optical imaging camera used on large ground-based telescopes for deep, high-resolution astronomical surveys.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3ce07788190a179705eb1b6c824 |
completed | April 20, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0575bfc9988190bc72525ab30cf498 |
completed | May 14, 2026, 7:12 a.m. |
| NEDg | Description generation | batch_6a057803e99481909c6ed82014a169d0 |
completed | May 14, 2026, 7:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05785d1e08819097299cf6d9e90035 |
completed | May 14, 2026, 7:23 a.m. |
Created at: April 10, 2026, 11:57 a.m.