Triple
T19376859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | He Saifei |
E484692
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Assassin |
—
|
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: The Assassin | Statement: [He Saifei, notableWork, The Assassin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Assassin Context triple: [He Saifei, notableWork, The Assassin]
-
A.
The Assassin
The Assassin is the alternative title of "Venetian Bird," a 1952 British film noir thriller directed by Ralph Thomas and set against the backdrop of postwar Venice.
-
B.
The Assassin
chosen
The Assassin is a 2015 Taiwanese wuxia film directed by Hou Hsiao-hsien, acclaimed for its visually stunning, meditative take on the martial arts genre.
-
C.
the Assassin
The Assassin is a central, enigmatic killer figure in the "Mad God" universe, embodying its dark, surreal, and violent themes.
-
D.
Assassin
Assassin is a rapper known for his energetic delivery and collaborations within the hip-hop and dancehall scenes.
-
E.
Assassin
Assassin is a stand-up comedy special by Margaret Cho known for its sharp political satire and candid social commentary.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a5cfbf48190ac60e3ffa6baa263 |
completed | April 20, 2026, 12:21 p.m. |
Created at: April 10, 2026, 1:35 p.m.