Triple
T21677216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Up Close & Personal |
E535001
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Kate Nelligan |
—
|
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 Nelligan | Statement: [Up Close & Personal, starring, Kate Nelligan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Nelligan Context triple: [Up Close & Personal, starring, Kate Nelligan]
-
A.
Kate Nelligan
chosen
Kate Nelligan is a Canadian actress acclaimed for her work in film, television, and theatre, noted for her intense dramatic performances and multiple award nominations.
-
B.
Kelly Kelleher
Kelly Kelleher is the protagonist of Joyce Carol Oates’s novel "Black Water," a young woman whose tragic encounter with a powerful politician mirrors the real-life Chappaquiddick incident.
-
C.
Bridget Tierney
Bridget Tierney is an actress known for her role in the television film "In the Gloaming."
-
D.
Kate Hennessy
Kate Hennessy is an American writer and the granddaughter of Catholic social activist Dorothy Day, known for her memoirs and work chronicling her family’s legacy.
-
E.
Kate Mullen
Kate Mullen is the central protagonist of the work "Ransom," around whom the main narrative and its conflicts revolve.
- 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef8a105b888190820b894d16c1ab77 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 16, 2026, 6:42 p.m.