Triple
T26008323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeffrey Maier |
E646820
|
entity |
| Predicate | attendedHighSchool |
P141059
|
FINISHED |
| Object | Northern Valley Regional High School at Old Tappan |
—
|
NE NERFINISHED |
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: Northern Valley Regional High School at Old Tappan | Statement: [Jeffrey Maier, attendedHighSchool, Northern Valley Regional High School at Old Tappan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attendedHighSchool Context triple: [Jeffrey Maier, attendedHighSchool, Northern Valley Regional High School at Old Tappan]
-
A.
attendedHighSchoolIn
chosen
Indicates that an entity completed or was enrolled in high school education in a specified location.
-
B.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
C.
hasSingleHighSchool
Indicates that an entity is associated with exactly one high school.
-
D.
hasNotableHighSchool
Indicates that an entity is associated with a high school that is particularly notable or significant in some recognized way.
-
E.
highSchoolStatus
Indicates the relationship between a person and their current or completed status in high school (e.g., enrolled, graduated, dropped out).
- 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_69e77e89d5848190b54352cdb74f6029 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f605b366f8819096534cffdd0aa509 |
completed | May 2, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69f4a10728e08190bc0b96c558740f51 |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 9:01 a.m.