Triple
T10382871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sissy Spacek |
E244684
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Virginia, United States |
E5410
|
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: Virginia, United States | Statement: [Sissy Spacek, residence, Virginia, United States]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Virginia, United States Context triple: [Sissy Spacek, residence, Virginia, United States]
-
A.
Virginia
Virginia is a small community located within the town of Georgina in Ontario, Canada.
-
B.
Virginia
chosen
Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American history, including being home to several early presidents and key Revolutionary and Civil War sites.
-
C.
Virginia
Virginia is a coastal township in Montserrado County, Liberia, known for its beaches and proximity to the capital, Monrovia.
-
D.
Washington, Virginia
Washington, Virginia is a small historic town in the foothills of the Blue Ridge Mountains known for its preserved 18th-century character and acclaimed dining, including The Inn at Little Washington.
-
E.
La Virginia
La Virginia is a municipality in western Colombia known for its location along the Cauca River and its role as a commercial and transport hub in the Risaralda Department.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e992d8e08190aaa9a04925f52ccc |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fba398b88190ae3223218bf53ca7 |
completed | April 9, 2026, 7:18 p.m. |
Created at: April 6, 2026, 12:04 p.m.