Triple
T18856641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fletcher Reede |
E461187
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object | Liar Liar |
—
|
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: Liar Liar | Statement: [Fletcher Reede, appearsIn, Liar Liar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liar Liar Context triple: [Fletcher Reede, appearsIn, Liar Liar]
-
A.
Liar Liar
chosen
Liar Liar is a 1997 comedy film starring Jim Carrey as a fast-talking lawyer magically compelled to tell the truth for 24 hours, leading to a series of chaotic and humorous consequences.
-
B.
Liar Liar
"Liar Liar" is a pop song by American singer Christina Grimmie that showcases her powerful vocals and emotive, piano-driven style.
-
C.
Hollywood Liar
"Hollywood Liar" is a song featured on the album *Inside Story*, likely characterized by themes of deception and the darker side of fame.
-
D.
Liar
"Liar" is a 1992 noise rock album by The Jesus Lizard, widely regarded as one of the band's most intense and critically acclaimed releases.
-
E.
Liar
"Liar" is a 2019 Latin pop-influenced single by Cuban-American singer Camila Cabello, known for its playful lyrics and brass-heavy, danceable production.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c05d0bb8819094d0447441f85b57 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 10, 2026, 11:57 a.m.