Triple
T14819113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taxi to the Dark Side |
E348397
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Eva Orner |
E348397
|
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: Eva Orner | Statement: [Taxi to the Dark Side, producer, Eva Orner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eva Orner Context triple: [Taxi to the Dark Side, producer, Eva Orner]
-
A.
Eva Orner
chosen
Eva Orner is an Australian documentary filmmaker and producer known for her hard-hitting political and human rights films, including the Academy Award-winning "Taxi to the Dark Side."
-
B.
Evelyn Baran
Evelyn Baran is best known as the wife of pioneering engineer Paul Baran, a key figure in the development of packet-switched networks and the internet.
-
C.
Paula Dobriansky
Paula Dobriansky is an American foreign policy expert and diplomat who has held several senior U.S. government positions, particularly in European and democracy-promotion affairs.
-
D.
Elka Ostrovsky
Elka Ostrovsky is a sharp-tongued, eccentric elderly woman and main character on the sitcom "Hot in Cleveland," portrayed by Betty White.
-
E.
Norah Lorkowski
Norah Lorkowski is a character from the film "Sunshine Cleaning," portrayed as the aimless, rebellious younger sister who joins her sibling in starting a crime-scene cleanup business.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe4cf38819090f25ef045351d5d |
completed | April 14, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9685aa5c8190b4e4d82af80f36f8 |
completed | May 9, 2026, 2:05 a.m. |
Created at: April 10, 2026, 1:50 a.m.