Triple
T11743534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonnie Plunkett |
E279212
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object | Mom |
E120569
|
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: Mom | Statement: [Bonnie Plunkett, appearsIn, Mom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mom Context triple: [Bonnie Plunkett, appearsIn, Mom]
-
A.
Mom
chosen
Mom is a popular American sitcom starring Allison Janney and Anna Faris that follows a dysfunctional mother-daughter duo in recovery from addiction.
-
B.
Mom
Mom is a recurring villain in the animated series Futurama, portrayed as the ruthless, foul-mouthed corporate matriarch who secretly controls the galaxy’s largest robot-manufacturing conglomerate.
-
C.
MOM
MOM is a post-nominal abbreviation used in Canada to denote a Member of the Order of Merit of the Police Forces, an honor recognizing exceptional service and leadership in policing.
-
D.
MOM
MOM is India’s first interplanetary spacecraft, a Mars orbiter launched by ISRO that made India the first Asian nation to reach Martian orbit.
-
E.
mother!
mother! is a 2017 psychological horror film written and directed by Darren Aronofsky, known for its allegorical narrative, intense performances, and polarizing reception.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f191388190bd6ef7e80c41ca48 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f019e4f0988190afe0b92f4c9d8073 |
completed | April 28, 2026, 2:22 a.m. |
Created at: April 8, 2026, 9:41 p.m.