Triple
T23045199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Creepshow 3 |
E573857
|
entity |
| Predicate | hasStorySegment |
P95980
|
FINISHED |
| Object | Alice |
—
|
NE NERFINISHED |
How this triple was built (4 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: Alice | Statement: [Creepshow 3, hasStorySegment, Alice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alice Context triple: [Creepshow 3, hasStorySegment, Alice]
-
A.
Alice
Alice is one of the given names of Anne, Princess Royal, the only daughter of Queen Elizabeth II and Prince Philip.
-
B.
Alice
Alice is an American sitcom that aired from the mid-1970s to the mid-1980s, following a widowed waitress working at a roadside diner and the quirky people in her life.
-
C.
Alice
Alice is the curious young girl who serves as the main protagonist of Disney’s animated film "Alice in Wonderland."
-
D.
Alice
Alice is the conventional placeholder name used to represent a generic sender or participant in cryptographic protocols and security examples.
-
E.
Alice
Alice Roosevelt Longworth was an influential American writer and socialite, the eldest child of President Theodore Roosevelt, known for her sharp wit and prominent role in Washington, D.C. society.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alice Target entity description: Alice is a character featured in one of the horror-comedy anthology segments of the film Creepshow 3.
-
A.
Alice
Alice is a central comedic character in the film "Mike and Dave Need Wedding Dates," known for her wild, unpredictable behavior as one of the women who answer the brothers’ ad for wedding dates.
-
B.
Alice
Alice is the central protagonist of the 2017 dark comedy film "Rough Night," around whom the chaotic bachelorette-party storyline revolves.
-
C.
Alice
Alice is the superhuman protagonist of the Resident Evil film series, known for battling bioengineered monsters and the Umbrella Corporation in a post-apocalyptic world.
-
D.
Alice
Alice is a fictional character from the Brazilian film "Samba," serving as one of the key figures in the story’s exploration of immigration and social struggle.
-
E.
Alice
Alice is a fictional criminal psychologist and brilliant, manipulative sociopath from the British TV series "Luther."
- F. None of above. chosen
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStorySegment Context triple: [Creepshow 3, hasStorySegment, Alice]
-
A.
hasNarrativeSegments
chosen
Indicates that an entity is composed of or associated with multiple distinct narrative segments or sections.
-
B.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
C.
hasSiblingInStory
Indicates that one character in a narrative has at least one sibling who also appears within the same story.
-
D.
hasStoryPath
Indicates that there exists a defined narrative route or sequence of events connecting one entity to another within a story or interactive experience.
-
E.
hasLeaderInStory
Indicates that one entity serves as the leader of another entity within the context of a specific story or narrative.
- F. None of above.
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_69e245b9c11481909d06c872214d21af |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1851811e08190a5af6a112687327e |
completed | April 29, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69ef89d5f71881908b9f9d0c8aab278c |
completed | April 27, 2026, 4:07 p.m. |
Created at: April 17, 2026, 3:54 p.m.