Triple
T30243893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Bourne (2016 film) score |
E769000
|
entity |
| Predicate | primaryCharacterAssociatedWith |
P88683
|
FINISHED |
| Object | Jason Bourne |
E39808
|
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: Jason Bourne | Statement: [Jason Bourne (2016 film) score, primaryCharacterAssociatedWith, Jason Bourne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCharacterAssociatedWith Context triple: [Jason Bourne (2016 film) score, primaryCharacterAssociatedWith, Jason Bourne]
-
A.
fictionalCharacterAssociatedWith
chosen
Indicates that there is a notable connection or association between a fictional character and another entity, such as a work, creator, or universe.
-
B.
associatedWithCharacterRole
Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
-
C.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
D.
relatedCharacter
Indicates that one character has a specified relationship or association with another character.
-
E.
laterMainCharacterOf
Indicates that one entity becomes the main character of a work at a later point in time, succeeding another main character.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a01e4ba62748190a4756689219b6269 |
completed | May 11, 2026, 2:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a276444b9ac8190a969266f4dcc0c3d |
completed | June 9, 2026, 12:54 a.m. |
| PD | Predicate disambiguation | batch_6a01e3fc2d908190a075c7c1549e5640 |
completed | May 11, 2026, 2:13 p.m. |
Created at: April 29, 2026, 7:39 p.m.