Triple
T9459593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max von Sydow |
E228106
|
entity |
| Predicate | nominatedFor |
P1791
|
FINISHED |
| Object |
Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close
The Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close is the Oscar nomination recognizing Max von Sydow’s acclaimed supporting performance in the 2011 drama film "Extremely Loud & Incredibly Close."
|
E801118
|
NE FINISHED |
How this triple was built (4 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: Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close | Statement: [Max von Sydow, nominatedFor, Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close Context triple: [Max von Sydow, nominatedFor, Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close]
-
A.
Academy Award for Best Supporting Actor for Nocturnal Animals
The Academy Award for Best Supporting Actor for "Nocturnal Animals" is the Oscar nomination recognizing Michael Shannon's acclaimed supporting performance in Tom Ford's 2016 psychological thriller film.
-
B.
Academy Award for Best Supporting Actor for Little Children
The Academy Award for Best Supporting Actor for Little Children is the Oscar nomination Jackie Earle Haley received for his acclaimed supporting performance in the 2006 drama film "Little Children."
-
C.
Academy Award for Best Supporting Actress for Up in the Air
The Academy Award for Best Supporting Actress for Up in the Air is the Oscar nomination recognizing Vera Farmiga’s acclaimed supporting performance in the 2009 drama film "Up in the Air."
-
D.
Boston Society of Film Critics Award for Best Supporting Actor
The Boston Society of Film Critics Award for Best Supporting Actor is an annual honor recognizing outstanding performances by male actors in supporting roles in films, as chosen by the Boston Society of Film Critics.
-
E.
Academy Award for Best Supporting Actress for Silver Linings Playbook
The Academy Award for Best Supporting Actress for Silver Linings Playbook is the Oscar nomination recognizing an actress’s supporting performance in the 2012 romantic comedy-drama film "Silver Linings Playbook."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close Triple: [Max von Sydow, nominatedFor, Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close]
Generated description
The Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close is the Oscar nomination recognizing Max von Sydow’s acclaimed supporting performance in the 2011 drama film "Extremely Loud & Incredibly Close."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close Target entity description: The Academy Award for Best Supporting Actor for Extremely Loud & Incredibly Close is the Oscar nomination recognizing Max von Sydow’s acclaimed supporting performance in the 2011 drama film "Extremely Loud & Incredibly Close."
-
A.
Academy Award for Best Supporting Actor for Nocturnal Animals
The Academy Award for Best Supporting Actor for "Nocturnal Animals" is the Oscar nomination recognizing Michael Shannon's acclaimed supporting performance in Tom Ford's 2016 psychological thriller film.
-
B.
Academy Award for Best Supporting Actor for Little Children
The Academy Award for Best Supporting Actor for Little Children is the Oscar nomination Jackie Earle Haley received for his acclaimed supporting performance in the 2006 drama film "Little Children."
-
C.
Academy Award for Best Supporting Actress for Up in the Air
The Academy Award for Best Supporting Actress for Up in the Air is the Oscar nomination recognizing Vera Farmiga’s acclaimed supporting performance in the 2009 drama film "Up in the Air."
-
D.
Boston Society of Film Critics Award for Best Supporting Actor
The Boston Society of Film Critics Award for Best Supporting Actor is an annual honor recognizing outstanding performances by male actors in supporting roles in films, as chosen by the Boston Society of Film Critics.
-
E.
Academy Award for Best Supporting Actress for Silver Linings Playbook
The Academy Award for Best Supporting Actress for Silver Linings Playbook is the Oscar nomination recognizing an actress’s supporting performance in the 2012 romantic comedy-drama film "Silver Linings Playbook."
- F. None of above. chosen
Provenance (5 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fc916348190aeb3874a89071677 |
completed | April 1, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122965aa48190bb35202b8dd0fdbd |
completed | April 4, 2026, 2:39 p.m. |
| NEDg | Description generation | batch_69d12474e91c8190b3f127a44fb0f345 |
completed | April 4, 2026, 2:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d12521921881909fa14b99c6dd5158 |
completed | April 4, 2026, 2:50 p.m. |
Created at: March 30, 2026, 7:52 p.m.