Triple
T15460212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Rossen |
E371877
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Rossen |
E1019103
|
NE FINISHED |
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: Rossen | Statement: [Daniel Rossen, familyName, Rossen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rossen Context triple: [Daniel Rossen, familyName, Rossen]
-
A.
Rossen
chosen
Rossen is a surname most notably associated with American screenwriter and director Robert Rossen, known for films such as "All the King's Men" and "The Hustler."
-
B.
Mark Rosman
Mark Rosman is an American film and television director and screenwriter best known for his work on family and teen-oriented movies and series, including projects for Disney.
-
C.
Ari Leschnikoff
Ari Leschnikoff was a Bulgarian-born tenor and entertainer best known as a member of the renowned German vocal group the Comedian Harmonists in the early 20th century.
-
D.
Nicholas Grodin
Nicholas Grodin is the son of the late American actor and comedian Charles Grodin.
-
E.
Victor Rasuk
Victor Rasuk is an American actor known for roles in films like "Lords of Dogtown" and "How to Make It in America," as well as supporting parts in major franchises.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f17663c8190b995c7c3129c90d6 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cfd76cc8190b3d8148ffe872887 |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 3:32 a.m.