Triple
T34034529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Miller |
E872752
|
entity |
| Predicate | setInSchool |
P178162
|
FINISHED |
| Object | McKinley High School |
—
|
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: McKinley High School | Statement: [Ken Miller, setInSchool, McKinley High School]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setInSchool Context triple: [Ken Miller, setInSchool, McKinley High School]
-
A.
statusInSchool
Indicates the role, standing, or level an individual holds within an educational institution (e.g., student, teacher, grade level, or enrollment status).
-
B.
schoolBelongsTo
Indicates that a particular school is owned by, affiliated with, or under the authority or jurisdiction of a specific organization, institution, or administrative entity.
-
C.
hasSchoolIn
Indicates that a school is located within or operates in a specified place or region.
-
D.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
E.
isSchoolFor
Indicates that one entity functions as an educational institution intended to serve, teach, or train the other entity.
- 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_69f349a2527c81909a7cd4bda94d70ad |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70c53062c8190b4cb7be22ab00bc7 |
completed | May 3, 2026, 8:50 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70b94784c8190970d654e066eb50d |
completed | May 3, 2026, 8:47 a.m. |
Created at: May 1, 2026, 1:51 a.m.