Triple
T2811011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean McVay |
E54168
|
entity |
| Predicate | highSchoolPositionPlayed |
P43739
|
FINISHED |
| Object | quarterback |
—
|
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: quarterback | Statement: [Sean McVay, highSchoolPositionPlayed, quarterback]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highSchoolPositionPlayed Context triple: [Sean McVay, highSchoolPositionPlayed, quarterback]
-
A.
positionPlayedInCollege
Indicates the specific playing position an individual held on a sports team during their college career.
-
B.
draftedFromHighSchool
Indicates that an individual was selected or recruited directly from high school, without first attending a higher-level institution such as a college or university.
-
C.
playedHighSchoolBasketballAt
Indicates that a person was a member of and participated on the basketball team of a particular high school.
-
D.
playedCollegeSport
Indicates that the subject participated in an organized college-level sport for the object institution.
-
E.
stateOfHighSchool
Indicates the U.S. state in which a given high school is located or operates.
- 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_69ab49dcee188190b5c6eca9ae9e3469 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde335b38819090c70d5e2ca14d79 |
completed | March 7, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde0f4c648190b9812e64f30c39da |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 9:59 p.m.