Triple
T13500749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airport (1970 film) |
E320880
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Jean Seberg |
E221884
|
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: Jean Seberg | Statement: [Airport (1970 film), stars, Jean Seberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean Seberg Context triple: [Airport (1970 film), stars, Jean Seberg]
-
A.
Jean Seberg
chosen
Jean Seberg was an American actress and French New Wave icon best known for her role in Jean-Luc Godard’s film "Breathless."
-
B.
Lisa Dillman
Lisa Dillman is an American playwright known for her contemporary stage works and as a notable alumna of the Playwrights Workshop.
-
C.
Sue Lyon
Sue Lyon was an American actress best known for her provocative title role in Stanley Kubrick’s film "Lolita" (1962).
-
D.
Patty McCormack
Patty McCormack is an American actress best known for her chilling childhood performance in the 1956 film "The Bad Seed," which earned her significant critical acclaim and early career honors.
-
E.
Nat Jaffe
Nat Jaffe is a central character in Michael Chabon’s novel "Telegraph Avenue," depicted as one of the intertwined figures navigating family, culture, and community in contemporary Oakland and Berkeley.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf50f4a48190a44fc537b78c32fd |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75487cb3c8190ab7f3bc36755b74c |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:43 p.m.