Triple
T22894952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Come See the Paradise |
E568146
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Stan Egi |
—
|
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: Stan Egi | Statement: [Come See the Paradise, starring, Stan Egi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stan Egi Context triple: [Come See the Paradise, starring, Stan Egi]
-
A.
Stan Egi
chosen
Stan Egi is an American actor known for his work in film and television, including roles in Asian American–themed productions.
-
B.
Ben Staad
Ben Staad is a loyal and courageous young nobleman who aids Prince Peter in Stephen King’s fantasy novel "The Eyes of the Dragon."
-
C.
Stan Steiner
Stan Steiner is an American educator and author known for his work in children's literature and literacy education.
-
D.
Don Stevens
Don Stevens is a notable individual recognized for achievements significant enough to be distinguished from others sharing the surname Stevens.
-
E.
Alan Ereira
Alan Ereira is a British historian, broadcaster, and documentary filmmaker known for his work on medieval history and indigenous cultures.
- 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f17fc83d688190a8ab5ea0aad1e7ec |
completed | April 29, 2026, 3:49 a.m. |
Created at: April 17, 2026, 3:40 p.m.