Triple
T27785536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mabel Chiltern |
E700948
|
entity |
| Predicate | relationshipToDeuteragonist |
P38921
|
FINISHED |
| Object | love interest of Lord Goring |
—
|
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: love interest of Lord Goring | Statement: [Mabel Chiltern, relationshipToDeuteragonist, love interest of Lord Goring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToDeuteragonist Context triple: [Mabel Chiltern, relationshipToDeuteragonist, love interest of Lord Goring]
-
A.
hasProtagonistRelationship
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
-
B.
relationshipWithAntagonist
Indicates a relationship or connection that an entity has with an opposing or adversarial figure in a narrative or context.
-
C.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
D.
relationshipToTheDude
Indicates the specific type of personal or social relationship that one entity has to the individual referred to as "the Dude."
-
E.
relatedCharacter
Indicates that one character has a specified relationship or association with 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_69ef6a50d8088190acbf3dfbb06d8091 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69ff90b673248190b4dda9e005642d17 |
completed | May 9, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69ff8d5bee1081909274052945e98a6f |
completed | May 9, 2026, 7:39 p.m. |
Created at: April 27, 2026, 5:24 p.m.