Triple
T34815535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plunder of the Sun |
E1003619
|
entity |
| Predicate | mainCharacterInvolvedIn |
P15562
|
FINISHED |
| Object | artifact smuggling |
—
|
LITERAL 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: artifact smuggling | Statement: [Plunder of the Sun, mainCharacterInvolvedIn, artifact smuggling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterInvolvedIn Context triple: [Plunder of the Sun, mainCharacterInvolvedIn, artifact smuggling]
-
A.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
B.
involvedActor
chosen
Indicates that an entity participates as an actor or participant in the referenced event, activity, or situation.
-
C.
mainCharactersAre
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
D.
meetsFictionalCharacter
Indicates that one entity encounters or comes into contact with a fictional 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 (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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: May 3, 2026, 3:59 p.m.