Triple
T12860430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimberly Williams-Paisley |
E307571
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kimberly |
E23752
|
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: Kimberly | Statement: [Kimberly Williams-Paisley, givenName, Kimberly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kimberly Context triple: [Kimberly Williams-Paisley, givenName, Kimberly]
-
A.
Kimberly
chosen
Kimberly is a feminine given name of English origin that has been widely used in the United States since the mid-20th century.
-
B.
Kimberly
Kimberly is a small city located in Idaho’s Magic Valley region, known for its agricultural surroundings and close proximity to Twin Falls.
-
C.
Kelli
Kelli is a feminine given name, typically considered a variant spelling of Kelly.
-
D.
Karenna
Karenna is an American lawyer, author, and environmental activist best known as the daughter of former U.S. Vice President Al Gore.
-
E.
Kayely
Kayely is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9708ba74881909b16c1e2ef5115db |
completed | April 10, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bac0c1081909217d865aa8bf9a3 |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:37 p.m.