Triple
T11050335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Astin |
E261227
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Christine Harrell |
E264402
|
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: Christine Harrell | Statement: [Elizabeth Astin, mother, Christine Harrell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christine Harrell Context triple: [Elizabeth Astin, mother, Christine Harrell]
-
A.
Christine Harrell
chosen
Christine Harrell is an American film producer and talent manager best known as the longtime wife of actor Sean Astin.
-
B.
Monika M. Richardson
Monika M. Richardson is the wife of American voice actor Kevin Michael Richardson.
-
C.
Larissa Weems
Larissa Weems is a character from the Netflix series "Wednesday," serving as the poised and enigmatic principal of Nevermore Academy.
-
D.
Cynthia Addai-Robinson
Cynthia Addai-Robinson is a British-American actress known for her roles in television series like "Spartacus," "Arrow," and "Power," as well as films such as "The Accountant."
-
E.
Kimberly J. Brown
Kimberly J. Brown is an American actress best known for playing Marnie Piper in Disney Channel’s Halloweentown film series.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79868c78881908c8e3672c05ae7ec |
completed | April 9, 2026, 12:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c851d5408190b12250a2a1322874 |
completed | April 18, 2026, 6:07 p.m. |
Created at: April 8, 2026, 9:26 p.m.