Triple
T21686895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smiley Face |
E535252
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Henry Winterstern
Henry Winterstern is a film producer known for his work on movies such as "Smiley Face."
|
E1496866
|
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: Henry Winterstern | Statement: [Smiley Face, producer, Henry Winterstern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henry Winterstern Context triple: [Smiley Face, producer, Henry Winterstern]
-
A.
Mark Weissenstern
Mark Weissenstern is an electronics industry figure best known as a founder of the semiconductor company Signetics.
-
B.
Andro Steinborn
Andro Steinborn is a film producer best known for his work on the psychological thriller "Funny Games U.S."
-
C.
Kristopher Van Varenberg
Kristopher Van Varenberg is a Belgian-American actor and filmmaker, best known as the son of action star Jean-Claude Van Damme and for appearing in several of his father's films.
-
D.
Felix Krull
Felix Krull is the charming, quick-witted con artist and social climber who narrates Thomas Mann’s picaresque novel "The Confessions of Felix Krull."
-
E.
Carl Hilpert
Carl Hilpert was a German Wehrmacht general during World War II who held several high-level commands on the Eastern Front.
- 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: Henry Winterstern Triple: [Smiley Face, producer, Henry Winterstern]
Generated description
Henry Winterstern is a film producer known for his work on movies such as "Smiley Face."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Henry Winterstern Target entity description: Henry Winterstern is a film producer known for his work on movies such as "Smiley Face."
-
A.
Mark Weissenstern
Mark Weissenstern is an electronics industry figure best known as a founder of the semiconductor company Signetics.
-
B.
Andro Steinborn
Andro Steinborn is a film producer best known for his work on the psychological thriller "Funny Games U.S."
-
C.
Kristopher Van Varenberg
Kristopher Van Varenberg is a Belgian-American actor and filmmaker, best known as the son of action star Jean-Claude Van Damme and for appearing in several of his father's films.
-
D.
Felix Krull
Felix Krull is the charming, quick-witted con artist and social climber who narrates Thomas Mann’s picaresque novel "The Confessions of Felix Krull."
-
E.
Carl Hilpert
Carl Hilpert was a German Wehrmacht general during World War II who held several high-level commands on the Eastern Front.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96cc31b8819086ca980521f94501 |
completed | April 27, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a1e20fc348190899995c0988d9cc5 |
completed | May 17, 2026, 7:59 p.m. |
| NEDg | Description generation | batch_6a0a1ef23b6c8190a0194719c34bb971 |
completed | May 17, 2026, 8:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a1fc13900819098ee66684dfdff95 |
completed | May 17, 2026, 8:06 p.m. |
Created at: April 16, 2026, 6:44 p.m.