Triple
T4758115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Molly Bloom's soliloquy |
E105635
|
entity |
| Predicate | hasCharacterRelation |
P38921
|
FINISHED |
| Object | wife of Leopold Bloom |
—
|
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: wife of Leopold Bloom | Statement: [Molly Bloom's soliloquy, hasCharacterRelation, wife of Leopold Bloom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacterRelation Context triple: [Molly Bloom's soliloquy, hasCharacterRelation, wife of Leopold Bloom]
-
A.
hasTitleCharacterRelation
Indicates a relationship where a title (such as a work or publication) is associated with or linked to a specific character appearing in it.
-
B.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
C.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
D.
hasProtagonistRelationship
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
-
E.
hasParentCharacter
Indicates that one character is the parent of another 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd6225c9488190afee5bb3619d0365 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.