Triple
T19907459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Print |
E478455
|
entity |
| Predicate | precedes |
P97
|
FINISHED |
| Object | The Camera |
—
|
NE NERFINISHED |
How this triple was built (2 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: The Camera | Statement: [The Print, precedes, The Camera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Camera Context triple: [The Print, precedes, The Camera]
-
A.
The Camera
chosen
The Camera is a seminal photography book by Ansel Adams that explores the technical and artistic use of cameras in creating expressive photographs.
-
B.
Camara
Camara is the given name of American actress and model Yaya DaCosta, known for her work in film, television, and fashion.
-
C.
Caméra One
Caméra One is a French film production company known for producing acclaimed art-house and auteur-driven movies.
-
D.
Camira
Camira is a residential suburb located within the Ipswich City Council area in South East Queensland, Australia.
-
E.
Camira
Camira is a compact family car model produced by Holden, the Australian subsidiary of General Motors, during the 1980s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6598cc5108190bca2a47c9f8ef70f |
completed | April 20, 2026, 4:51 p.m. |
Created at: April 10, 2026, 1:52 p.m.