Triple
T13097293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Cooke |
E310623
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cooke |
E65201
|
NE FINISHED |
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: Cooke | Statement: [Jane Cooke, familyName, Cooke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cooke Context triple: [Jane Cooke, familyName, Cooke]
-
A.
Cooke
chosen
Cooke is a surname of English origin, often considered a variant spelling of "Cook."
-
B.
Cooke Enterprises
Cooke Enterprises was a private business conglomerate owned and operated by sports and media magnate Jack Kent Cooke, encompassing his diverse investments and ventures.
-
C.
Optica
Optica is a leading scientific society dedicated to advancing the study and application of optics and photonics worldwide.
-
D.
Carl Zeiss Tessar
Carl Zeiss Tessar is a classic high-quality photographic lens design, renowned for its sharpness and compact construction and widely used in cameras and mobile devices.
-
E.
Bell & Howell
Bell & Howell is an American company historically known for producing motion picture cameras, projectors, and other audiovisual and imaging equipment.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d9814e88a0819088418c792ce7aa57 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e275df6c819096bb59e64df35216 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 9:04 p.m.