Triple
T22198831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juno (2007 film) |
E548619
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Lianne Halfon |
—
|
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: Lianne Halfon | Statement: [Juno (2007 film), producer, Lianne Halfon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lianne Halfon Context triple: [Juno (2007 film), producer, Lianne Halfon]
-
A.
Lianne Halfon
chosen
Lianne Halfon is an American film producer known for her work on acclaimed independent films such as "Juno," "Young Adult," and "Ghost World."
-
B.
Rachel Fannan
Rachel Fannan is an American singer and songwriter best known for her work in psychedelic and indie rock projects, including collaborations with bands like Sleepy Sun and Black Mountain.
-
C.
Lianne Neudecker
Lianne Neudecker is a character associated with Hammad, likely appearing in the same narrative or production as a supporting or related figure.
-
D.
Tanya Biank
Tanya Biank is an American journalist and author known for her in-depth reporting and books on the lives and challenges of military families.
-
E.
Emily Ferranti
Emily Ferranti is an actress known for playing Nessarose in productions of the musical "Wicked."
- 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12ae98808819081582a57bca6312b |
completed | April 28, 2026, 9:47 p.m. |
Created at: April 16, 2026, 8:36 p.m.