Triple
T1406873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swoosie Kurtz |
E31712
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Swoosie |
E161163
|
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: Swoosie | Statement: [Swoosie Kurtz, givenName, Swoosie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swoosie Context triple: [Swoosie Kurtz, givenName, Swoosie]
-
A.
Swoosie Kurtz
chosen
Swoosie Kurtz is an American actress known for her work on stage, film, and television, including acclaimed performances in "Sisters," "Pushing Daisies," and numerous Broadway productions.
-
B.
Suzie Chapstick
Suzie Chapstick is the advertising nickname of Suzy Chaffee, a former Olympic skier and popular 1970s TV commercial personality known for promoting ChapStick lip balm.
-
C.
Charlene
Charlene is a feminine given name derived from the male name Charles.
-
D.
Suzanne
"Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
-
E.
Chantay Savage
Chantay Savage is an American R&B singer and songwriter best known for her soulful vocals and 1990s hits like her cover of "I Will Survive."
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3be10348190ade8a73780d2c008 |
completed | March 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad015839908190b7f9f6c79dcc0367 |
completed | March 8, 2026, 4:55 a.m. |
Created at: March 1, 2026, 7:59 p.m.