Triple
T14520970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'm Not There |
E340649
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Oren Moverman |
E102599
|
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: Oren Moverman | Statement: [I'm Not There, writer, Oren Moverman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oren Moverman Context triple: [I'm Not There, writer, Oren Moverman]
-
A.
Oren Moverman
chosen
Oren Moverman is an Israeli-American screenwriter and director known for his work on acclaimed films such as "I'm Not There," "The Messenger," and "Rampart."
-
B.
Des McAnuff
Des McAnuff is a Tony Award–winning Canadian-American director and producer best known for his work on major Broadway musicals such as "Jersey Boys" and "Big River."
-
C.
J. C. Chandor
J. C. Chandor is an American filmmaker known for writing and directing character-driven dramas and thrillers such as "Margin Call," "All Is Lost," and "A Most Violent Year."
-
D.
Todd Field
Todd Field is an American filmmaker, screenwriter, and former actor best known for directing critically acclaimed films such as "In the Bedroom," "Little Children," and "Tár."
-
E.
Martin Arjovsky
Martin Arjovsky is a machine learning researcher best known for introducing the Wasserstein GAN, a generative adversarial network variant that improves training stability and sample quality.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a72cff08190878b4bed9b0b5eb5 |
completed | April 14, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a4b71688190ae9ebccdc81d09f8 |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.