Triple
T29521259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western State Normal School |
E748939
|
entity |
| Predicate | hadAlumni |
P51
|
FINISHED |
| Object | public school teachers in Michigan |
—
|
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: public school teachers in Michigan | Statement: [Western State Normal School, hadAlumni, public school teachers in Michigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadAlumni Context triple: [Western State Normal School, hadAlumni, public school teachers in Michigan]
-
A.
hasAlumni
chosen
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
B.
hadAlumniRole
Indicates that an entity previously held a role or position as an alumnus/alumna of another entity (such as an institution or organization).
-
C.
hasAlumnusWhoBecame
Indicates that an institution has at least one alumnus who later attained or assumed a specified role, position, or status.
-
D.
namedAfterAlumnusOf
Indicates that one entity is named in honor of a person who is an alumnus of another specified institution or organization.
-
E.
hasProfessionalAlumni
Indicates that an institution or organization has alumni who have gone on to work in a specified profession or professional field.
- 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_69f0bd46d99c81908ba9d01cc1dbef7d |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66c9973b08190bbb12bd759f0578e |
completed | May 2, 2026, 9:28 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 4:41 p.m.