Triple
T12657527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy New Year (1987 film) |
E302323
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Charlie
Charlie is the protagonist of the 1987 film "Happy New Year," around whom the movie’s central story and character development revolve.
|
E995361
|
NE FINISHED |
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: Charlie | Statement: [Happy New Year (1987 film), mainCharacter, Charlie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charlie Context triple: [Happy New Year (1987 film), mainCharacter, Charlie]
-
A.
Charlie
Charlie was the third nuclear test in the U.S. Operation Crossroads series, planned as an underwater detonation to study the effects of nuclear weapons on naval vessels.
-
B.
Charlie
Charlie is the yellow-suited captain and one of the three main playable leaders in Pikmin 3, known for commanding Pikmin on the planet PNF-404.
-
C.
Charlie
Charlie is the central protagonist of the apocalyptic horror film "Legion" (2010), a pregnant waitress whose unborn child is believed to be humanity’s last hope.
-
D.
Charlie
Charlie is the given name of English actor and producer Charlie Bewley, known for his role as Demetri in the Twilight film series.
-
E.
Charlie
Charlie is a classic Revlon perfume line known for its accessible, youthful, and independent image, especially popular from the 1970s onward.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Charlie Triple: [Happy New Year (1987 film), mainCharacter, Charlie]
Generated description
Charlie is the protagonist of the 1987 film "Happy New Year," around whom the movie’s central story and character development revolve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charlie Target entity description: Charlie is the protagonist of the 1987 film "Happy New Year," around whom the movie’s central story and character development revolve.
-
A.
Charlie
Charlie is a central character in the romantic comedy film "French Kiss," serving as the unfaithful fiancé whose actions set the story’s events in motion.
-
B.
Charlie
Charlie is the protagonist of the story "His New Job," a 1915 silent comedy film written, directed by, and starring Charlie Chaplin.
-
C.
Charlie
Charlie is the kind-hearted young protagonist of Roald Dahl's novel "Charlie and the Chocolate Factory."
-
D.
Charlie
Charlie is a character featured in the work titled "Seascape."
-
E.
Charlie
Charlie is the central protagonist of the apocalyptic horror film "Legion" (2010), a pregnant waitress whose unborn child is believed to be humanity’s last hope.
- F. None of above. chosen
Provenance (5 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961636db8819099c438b24bcfd866 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f668832c7081909eb75429efba493e |
completed | May 2, 2026, 9:11 p.m. |
| NEDg | Description generation | batch_69f6697e3a688190abd025df1112feba |
completed | May 2, 2026, 9:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f66a9230608190bfe99290ca1679fa |
completed | May 2, 2026, 9:20 p.m. |
Created at: April 9, 2026, 5:19 p.m.