Triple
T5128224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Schwartzman |
E115633
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Schwartzman |
E138073
|
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: Schwartzman | Statement: [Jason Schwartzman, familyName, Schwartzman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwartzman Context triple: [Jason Schwartzman, familyName, Schwartzman]
-
A.
Marco Etcheverry
Marco Etcheverry is a retired Bolivian attacking midfielder renowned as one of Major League Soccer’s early stars and a key playmaker for D.C. United in the late 1990s.
-
B.
Molinari
Molinari is an Italian surname commonly associated with families whose ancestors worked as millers.
-
C.
Max Da Costa
Max Da Costa is the protagonist of the sci-fi film "Elysium," a former car thief who undertakes a dangerous mission to reach a luxurious space habitat and challenge its oppressive class system.
-
D.
Sebastian Gutierrez
Sebastian Gutierrez is a Venezuelan-American filmmaker known for writing and directing independent films such as "Judas Kiss," "Women in Trouble," and "Elektra Luxx."
-
E.
John Schwartzman
chosen
John Schwartzman is an American cinematographer known for his work on major Hollywood films, including action blockbusters and large-scale studio productions.
- 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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd782428a081909583c7f368226daf |
completed | March 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4beb7b48190a2f4e41a13fdd5f3 |
completed | March 21, 2026, 4:18 p.m. |
Created at: March 20, 2026, 1:42 p.m.