Triple
T18690345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Hinkle |
E456978
|
entity |
| Predicate | storySettingMedium |
P73019
|
FINISHED |
| Object | American professional football game |
—
|
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: American professional football game | Statement: [Harry Hinkle, storySettingMedium, American professional football game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storySettingMedium Context triple: [Harry Hinkle, storySettingMedium, American professional football game]
-
A.
storySettingEvent
Indicates that an event takes place within, or helps define, the setting or background context of a story.
-
B.
storyMedium
chosen
Indicates the medium or format through which a story is conveyed (e.g., book, film, audio).
-
C.
storyWorld
Indicates the fictional universe or narrative setting within which a story, event, or character exists or takes place.
-
D.
narrativeSettingOfWork
Indicates that a particular place, time, or context serves as the narrative setting in which a work’s story or events occur.
-
E.
storyEngine
Indicates that one entity functions as a narrative-generating or plot-controlling mechanism for another entity or set of events.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e28e5c8190b0033c1667d50e05 |
completed | April 19, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.