Triple
T31257126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riff Lorton |
E797005
|
entity |
| Predicate | influencedCharacterizationOf |
P157823
|
FINISHED |
| Object | Riff’s personality in West Side Story |
—
|
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: Riff’s personality in West Side Story | Statement: [Riff Lorton, influencedCharacterizationOf, Riff’s personality in West Side Story]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedCharacterizationOf Context triple: [Riff Lorton, influencedCharacterizationOf, Riff’s personality in West Side Story]
-
A.
influencesCharacter
Indicates that one entity affects, shapes, or alters the traits, behavior, or development of another entity’s character.
-
B.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
C.
stanceCharacterization
Indicates how an entity’s attitude, position, or viewpoint toward another entity, claim, or issue is characterized.
-
D.
influenceOf
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
E.
influencedAspectOf
chosen
Indicates that one entity has affected, shaped, or altered a particular aspect or component of another entity.
- 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_69f224dd5fdc81908a4cd24917b67668 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: April 29, 2026, 9:12 p.m.