Triple
T27234143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prisoners of the Sun |
E682229
|
entity |
| Predicate | featuresCharacterRescue |
P193460
|
FINISHED |
| Object | Professor Calculus |
—
|
NE NERFINISHED |
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: Professor Calculus | Statement: [Prisoners of the Sun, featuresCharacterRescue, Professor Calculus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCharacterRescue Context triple: [Prisoners of the Sun, featuresCharacterRescue, Professor Calculus]
-
A.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
B.
featuresReturningCharacterFrom
Indicates that a work includes the reappearance of a character who previously appeared in the referenced source work.
-
C.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
D.
featuresCharactersFrom
Indicates that one entity (such as a work or production) includes or presents characters originating from another entity.
-
E.
hasRescueTeamCharacter
Indicates that an entity includes or is associated with a character who is part of a rescue team.
- F. None of above. chosen
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_69eefacdad7881908b7bca61c90a1a1e |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
| PDg | Predicate description generation | batch_69fd485e0c20819099756b4fe39ac326 |
completed | May 8, 2026, 2:20 a.m. |
Created at: April 27, 2026, 9:47 a.m.