Triple
T9217585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebastian Wilder |
E221278
|
entity |
| Predicate | influencesWithinStory |
P69465
|
FINISHED |
| Object | inspires Mia Dolan to pursue acting more seriously |
—
|
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: inspires Mia Dolan to pursue acting more seriously | Statement: [Sebastian Wilder, influencesWithinStory, inspires Mia Dolan to pursue acting more seriously]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesWithinStory Context triple: [Sebastian Wilder, influencesWithinStory, inspires Mia Dolan to pursue acting more seriously]
-
A.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
B.
influencesCharacter
Indicates that one entity affects, shapes, or alters the traits, behavior, or development of another entity’s character.
-
C.
influencedDiscussionOf
Indicates that one entity had an effect on the way another entity was discussed, framed, or debated.
-
D.
influentialFrom
chosen
Indicates that one entity has exerted influence on another, contributing to or shaping the latter’s ideas, behavior, or development.
-
E.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda0ae3d081908ff3f5dab52df5ae |
completed | April 1, 2026, 8:40 a.m. |
| PD | Predicate disambiguation | batch_69cc660ce23c81909c7bbe10f4a05f36 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:27 p.m.