Triple
T31926232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose Sees Red |
E815119
|
entity |
| Predicate | otherMainCharacterNationality |
P146684
|
FINISHED |
| Object | Soviet |
—
|
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: Soviet | Statement: [Rose Sees Red, otherMainCharacterNationality, Soviet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherMainCharacterNationality Context triple: [Rose Sees Red, otherMainCharacterNationality, Soviet]
-
A.
protagonistNationality
Indicates the country or national identity to which the protagonist of a work is associated or belongs.
-
B.
laterMainCharacterOf
Indicates that one entity becomes the main character of a work at a later point in time, succeeding another main character.
-
C.
protagonistEthnicity
Indicates the ethnic background or cultural heritage associated with a work’s main character.
-
D.
hasMainCharacterFrom
chosen
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
E.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
- 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_69f348f1df848190851bbfb988da3414 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 12:03 a.m.