Triple
T36558287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Henry, Ohio |
E901753
|
entity |
| Predicate | hasHighSchoolAthletics |
P54
|
FINISHED |
| Object | football program |
—
|
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: football program | Statement: [St. Henry, Ohio, hasHighSchoolAthletics, football program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighSchoolAthletics Context triple: [St. Henry, Ohio, hasHighSchoolAthletics, football program]
-
A.
hasAthletics
chosen
Indicates that an entity participates in, is associated with, or offers athletics-related activities or programs.
-
B.
hasNotableHighSchool
Indicates that an entity is associated with a high school that is particularly notable or significant in some recognized way.
-
C.
hasAthleticLevel
Indicates the degree or category of athletic ability, fitness, or performance associated with an entity.
-
D.
hasHighSchoolDivision
Indicates that an entity includes, is associated with, or operates a high school-level division or section within its organizational structure.
-
E.
playedHighSchoolBasketballAt
Indicates that a person was a member of and participated on the basketball team of a particular high school.
- 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_69f76e634e9481908c9ba1b87ab87c26 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff691f5ae481908597ce245188d31c |
completed | May 9, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69ff67ceeeb081909fd00cad166c4b6a |
completed | May 9, 2026, 4:58 p.m. |
Created at: May 3, 2026, 4:11 p.m.