Triple
T14925116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Hay |
E371612
|
entity |
| Predicate | represented |
P192
|
FINISHED |
| Object | Virginia |
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 | Statement: [James Hay, represented, Virginia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Virginia Context triple: [James Hay, represented, Virginia]
-
A.
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.
-
B.
Virginia
Virginia is a small community located within the town of Georgina in Ontario, Canada.
-
C.
Virginia
Virginia is a coastal township in Montserrado County, Liberia, known for its beaches and proximity to the capital, Monrovia.
-
D.
Virginia
Virginia is a character in the classic French farce "Il cappello di paglia di Firenze" ("The Florentine Straw Hat"), around whom part of the play’s romantic and comedic misunderstandings revolve.
-
E.
Virginia
Virginia is the birth name of legendary American country music singer Patsy Cline, renowned for her rich contralto voice and crossover hits in the late 1950s and early 1960s.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded633da0c8190b39f606212e48e71 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e86ce888190b03056db39438701 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 2:35 a.m.