Triple
T10256009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carol Guzy |
E240467
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Carol Guzy |
E240467
|
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: Carol Guzy | Statement: [Carol Guzy, name, Carol Guzy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carol Guzy Context triple: [Carol Guzy, name, Carol Guzy]
-
A.
Carol Guzy
chosen
Carol Guzy is an acclaimed American photojournalist renowned for her powerful, empathetic coverage of human suffering and global crises, and one of the few photographers to have won multiple Pulitzer Prizes.
-
B.
Carol Stevens
Carol Stevens is best known as one of the former wives of American novelist and journalist Norman Mailer.
-
C.
Diane Szalinski
Diane Szalinski is a character from the "Honey, I Shrunk the Kids" franchise, known as the practical and caring wife of eccentric inventor Wayne Szalinski.
-
D.
Carol Hagen
Carol Hagen is an American real estate agent best known as the wife of NBC Nightly News anchor Lester Holt.
-
E.
Gail Klintworth
Gail Klintworth is a business leader known for her senior roles in global consumer goods companies and her work advancing responsible, sustainable business practices.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d24c69ac81908b4da53d13407ac8 |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e437d4481908a722a6648b62b39 |
completed | April 10, 2026, 8:32 p.m. |
Created at: April 6, 2026, 11:30 a.m.