Triple
T15122533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pattie Mallette |
E361203
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Pattie Mallette |
E361203
|
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: Pattie Mallette | Statement: [Pattie Mallette, name, Pattie Mallette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pattie Mallette Context triple: [Pattie Mallette, name, Pattie Mallette]
-
A.
Pattie Mallette
chosen
Pattie Mallette is a Canadian author and film producer best known as the mother of pop singer Justin Bieber.
-
B.
Tawny Newsome
Tawny Newsome is an American actress, comedian, and musician best known for her comedic roles and voice work, including starring in the animated series Star Trek: Lower Decks.
-
C.
Pam Bryant
Pam Bryant is an American woman best known as the mother of the late NBA superstar Kobe Bryant.
-
D.
Wendy Harris
Wendy Harris is a character known for being the mother figure in the context of the work in which she appears.
-
E.
Madeline Manning
Madeline Manning is an American middle-distance runner and Olympic gold medalist renowned for her achievements in the 800 meters.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0059f69a881909929a037a0eef702 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7f4abd08190b47c9daff2921919 |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 3:06 a.m.