Triple
T23467744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Tucci |
E569141
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Kate Tucci |
—
|
NE NERFINISHED |
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: Kate Tucci | Statement: [Kate Tucci, name, Kate Tucci]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Tucci Context triple: [Kate Tucci, name, Kate Tucci]
-
A.
Kate Tucci
chosen
Kate Tucci was the late wife of actor Stanley Tucci, known for her work as a social worker and producer and for largely staying out of the public spotlight.
-
B.
Addie Wolff
Addie Wolff was the wife of prominent American investment banker and philanthropist Otto H. Kahn.
-
C.
Christine Tucci
Christine Tucci is an American actress known for her work in film and television, including roles in projects like "Big Fat Liar" and "MDs."
-
D.
Carrie MacLemore
Carrie MacLemore is an American actress best known for her role in Whit Stillman’s comedy film "Damsels in Distress."
-
E.
Mitchell Alsup
Mitchell Alsup is a computer engineer best known as one of the founders of Transmeta, a company that developed innovative low-power microprocessor technologies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a6fd280c81908aae05f0851466eb |
completed | April 29, 2026, 6:36 a.m. |
Created at: April 17, 2026, 5:54 p.m.