Triple
T10311343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Tilly |
E241896
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Meg Tilly |
E268050
|
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: Meg Tilly | Statement: [Jennifer Tilly, sibling, Meg Tilly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meg Tilly Context triple: [Jennifer Tilly, sibling, Meg Tilly]
-
A.
Meg Tilly
chosen
Meg Tilly is a Canadian-American actress and novelist best known for her Academy Award–nominated performance in the film "Agnes of God."
-
B.
Maria Bello
Maria Bello is an American actress known for her versatile roles in film and television, including performances in projects like "A History of Violence," "ER," and "NCIS."
-
C.
Eliza Scanlen
Eliza Scanlen is an Australian actress known for her roles in film and television, including prominent performances in projects like "Sharp Objects" and "Little Women."
-
D.
Emily Alyn Lind
Emily Alyn Lind is an American actress known for her roles in film and television, including playing the young Amanda Clarke on the TV series "Revenge."
-
E.
Melissa Hudson
Melissa Hudson is known as the daughter of Stanley Hudson, a character from the American television series "The Office."
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d32ac6c08190b23eb042b3ec284a |
completed | April 7, 2026, 9:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d794ddbd9081909a534b29b3f75774 |
completed | April 9, 2026, noon |
Created at: April 6, 2026, 11:47 a.m.