Triple
T14990693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vega |
E373825
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Suzanne Vega |
E209595
|
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: Suzanne Vega | Statement: [Vega, hasNotableBearer, Suzanne Vega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suzanne Vega Context triple: [Vega, hasNotableBearer, Suzanne Vega]
-
A.
Suzanne Vega
chosen
Suzanne Vega is an American singer-songwriter known for her literate, folk-inspired songs such as "Luka" and "Tom's Diner," which gained prominence in the 1980s and 1990s.
-
B.
Jane Siberry
Jane Siberry is a Canadian singer-songwriter known for her eclectic, art-pop compositions and distinctive, ethereal vocal style.
-
C.
Susan Crow
Susan Crow is an American former teacher and philanthropist best known as the third wife and longtime partner of legendary singer Tony Bennett.
-
D.
Julee Cruise
Julee Cruise was an American singer and actress best known for her ethereal vocal work on the "Twin Peaks" soundtrack and other David Lynch projects.
-
E.
Laura Timmins
Laura Timmins is the young, observant heroine of the British period drama "Lark Rise to Candleford," whose move from her rural village to a nearby market town frames the series’ coming-of-age narrative.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded715db408190b44e8a8452c79764 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe969683348190bb4688f24227af88 |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:53 a.m.