Triple
T2943079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Helfrich |
E79432
|
entity |
| Predicate | seasonCoached |
P10045
|
FINISHED |
| Object | 2014 college football season |
—
|
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: 2014 college football season | Statement: [Mark Helfrich, seasonCoached, 2014 college football season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasonCoached Context triple: [Mark Helfrich, seasonCoached, 2014 college football season]
-
A.
leagueCoachedIn
Indicates the league in which a person or coach has coached a team.
-
B.
hasCoachedFor
chosen
Indicates that one entity has served in a coaching role for another entity, such as a team, organization, or individual.
-
C.
yearsActiveAsCoach
Indicates the span of time, typically in years, during which an individual has served in a coaching role.
-
D.
bowlGamesCoached
Indicates the number of postseason bowl games in which a coach has served as the head coach for a team.
-
E.
coachOfYearSeason
Indicates that a person was recognized as the coach of the year for a specific sports season.
- 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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9871fc908190ad90e5b01b476b3f |
completed | March 8, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69ad96088fb481909976b436c2b729d9 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:56 p.m.