Triple
T15911196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RUF/NEKS |
E385850
|
entity |
| Predicate | activityContext |
P121032
|
FINISHED |
| Object | college football games |
—
|
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: college football games | Statement: [RUF/NEKS, activityContext, college football games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: activityContext Context triple: [RUF/NEKS, activityContext, college football games]
-
A.
activityStartContext
Indicates the circumstances, conditions, or situation present at the moment an activity begins.
-
B.
activity
Indicates that an entity is engaged in or performing a particular action, behavior, or process.
-
C.
activityDomain
Indicates the general field, sector, or area of activity within which an entity operates or performs its main actions.
-
D.
activityType
Indicates the specific kind or category of action or event that an entity is engaged in or associated with.
-
E.
activityTheme
Indicates that an activity is centered around, focused on, or characterized by a particular theme.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:52 a.m.