Triple
T21654862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diane Whittlesey |
E534432
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Emerald City |
—
|
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: Emerald City | Statement: [Diane Whittlesey, workLocation, Emerald City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emerald City Context triple: [Diane Whittlesey, workLocation, Emerald City]
-
A.
Emerald City
Emerald City is a popular nickname for Seattle, highlighting the city's lush greenery and evergreen landscapes.
-
B.
Emerald City
Emerald City is the dazzling, green-hued capital of the Land of Oz and the central destination in L. Frank Baum’s classic tale "The Wonderful Wizard of Oz."
-
C.
Emerald City
Emerald City is a dark, modern television reimagining of L. Frank Baum’s Oz stories, blending fantasy and political intrigue.
-
D.
Emerald City
chosen
Emerald City is the experimental, tightly controlled cell block featured in the television series "Oz," designed to test unconventional approaches to prison management and inmate rehabilitation.
-
E.
Emerald City
Emerald City is a satirical Australian stage play by David Williamson that explores the ambitions and moral compromises of the film and publishing industries in Sydney.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef59176b28819092384fc5f8968022 |
completed | April 27, 2026, 12:39 p.m. |
Created at: April 16, 2026, 6:36 p.m.