Triple
T33548956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Picture (for Slumdog Millionaire, as co-producer) |
E859281
|
entity |
| Predicate | associatedSourceMaterialAuthor |
P36855
|
FINISHED |
| Object | Vikas Swarup |
E243948
|
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: Vikas Swarup | Statement: [Academy Award for Best Picture (for Slumdog Millionaire, as co-producer), associatedSourceMaterialAuthor, Vikas Swarup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedSourceMaterialAuthor Context triple: [Academy Award for Best Picture (for Slumdog Millionaire, as co-producer), associatedSourceMaterialAuthor, Vikas Swarup]
-
A.
hasAuthorOfSourceMaterial
Indicates that one entity is the creator or writer of the original source material on which another entity is based.
-
B.
anonymousAuthorOfSourceWork
Indicates that a person is the (unidentified or unnamed) author of a given source work.
-
C.
originalAuthorOfSource
chosen
Indicates that an entity is the original creator or author of a given source or work.
-
D.
authorOrigin
Indicates that an author has a specific place, region, or country as their origin or background.
-
E.
subjectRelationToAuthor
Indicates the relationship or connection that the subject has to the author.
- F. None of above.
Provenance (4 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_69f3497a5be08190a39b12736899e034 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a363c7d624c8190a4c8f1549286ae5c |
completed | June 20, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:39 a.m.