Triple
T15863341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwen Verdon |
E384646
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gwyneth |
E303076
|
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: Gwyneth | Statement: [Gwen Verdon, givenName, Gwyneth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gwyneth Context triple: [Gwen Verdon, givenName, Gwyneth]
-
A.
Gwyneth
chosen
Gwyneth is a feminine given name most notably borne by American actress and entrepreneur Gwyneth Paltrow.
-
B.
Gwyneth Bevan
Gwyneth Bevan is a notable individual associated with the surname Bevan, recognized as a distinguished bearer of that name.
-
C.
Miss Gwyneth Harridan
Miss Gwyneth Harridan is the strict, competitive head of an elite preschool who serves as the main antagonist in the family comedy film "Daddy Day Care."
-
D.
Gwyneth Williams
Gwyneth Williams is a British media executive best known for her role as Controller of BBC Radio 4 and BBC Radio 4 Extra.
-
E.
Gwyneth Powell
Gwyneth Powell was an English actress best known for her role as headmistress Mrs. McClusky in the long-running BBC school drama "Grange Hill."
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1555d38fc8190bd8820bb5b238b71 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa945d9808190a65f5182db341393 |
completed | May 9, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.