Triple
T22246885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Bad Moms Christmas |
E549866
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Kiki |
—
|
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: Kiki | Statement: [A Bad Moms Christmas, featuresCharacter, Kiki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiki Context triple: [A Bad Moms Christmas, featuresCharacter, Kiki]
-
A.
Kiki
Kiki is a Japanese actress best known internationally for her role as Miko Otomo in the television series "Heroes Reborn."
-
B.
Kiki
chosen
Kiki is one of the central overworked and underappreciated mothers in the comedy film "Bad Moms," known for her shy, anxious personality and eventual rebellious transformation.
-
C.
Kiki
Kiki was the nickname of Hazen "Kiki" Cuyler, a Hall of Fame Major League Baseball outfielder known for his speed and hitting in the 1920s and 1930s.
-
D.
Kiki
Kiki is the enigmatic female protagonist of Haruki Murakami’s novel "Dance Dance Dance," whose mysterious presence drives the narrator’s search through a surreal, dreamlike Tokyo.
-
E.
Let’s Have a Kiki
"Let’s Have a Kiki" is a campy, spoken-word-driven dance-pop song by Scissor Sisters that became a queer club anthem and viral cult favorite.
- 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f13218d1f88190b64b7f301328fa98 |
completed | April 28, 2026, 10:18 p.m. |
Created at: April 16, 2026, 8:38 p.m.