Triple
T20365193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Stafford |
E496888
|
entity |
| Predicate | wasTopHighSchoolRecruit |
P139856
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Matthew Stafford, wasTopHighSchoolRecruit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasTopHighSchoolRecruit Context triple: [Matthew Stafford, wasTopHighSchoolRecruit, true]
-
A.
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.
-
B.
hasNotableHighSchool
Indicates that an entity is associated with a high school that is particularly notable or significant in some recognized way.
-
C.
playedForCollegeTeamUntil
Indicates that an individual was a member of and played for a specific college team up to (and including) a particular end date or season.
-
D.
formerHighSchool
Indicates that one entity previously attended or was enrolled at the other entity as their high school.
-
E.
namedForCollege
Indicates that an entity is named after or in honor of a particular college.
- 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_69e0b4a4f9b081908a5a021919c21ccb |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67870f4448190ab63cbe03542de21 |
completed | April 20, 2026, 7:03 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:26 a.m.