Triple
T1100432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Seaborn |
E24365
|
entity |
| Predicate | storyline |
P24126
|
FINISHED |
| Object | runs for Congress in California |
—
|
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: runs for Congress in California | Statement: [Sam Seaborn, storyline, runs for Congress in California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyline Context triple: [Sam Seaborn, storyline, runs for Congress in California]
-
A.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
-
B.
storyFunction
Indicates that one entity serves a particular narrative role or function within the story structure of another entity.
-
C.
narrativeType
Indicates the specific kind or category of narrative (e.g., genre, structural form, or storytelling mode) associated with an entity.
-
D.
narrativeFrame
Indicates the overarching narrative context or perspective within which events, actions, or relationships are presented or interpreted.
-
E.
narrativeStyle
Indicates how a narrative is told, such as the point of view, tone, and structural approach used to present a story or account.
- F. None of above. chosen
Provenance (4 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c079f48190a0e0ddda182f7a01 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b745ef3481909a7ce4647c8567b3 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8f1097881908932d7eea4331917 |
completed | March 1, 2026, 10:08 p.m. |
Created at: March 1, 2026, 7:43 p.m.