Triple
T31340053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Free City College program in San Francisco |
E799281
|
entity |
| Predicate | institutionTypeCovered |
P117899
|
FINISHED |
| Object | public community college |
—
|
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 community college | Statement: [Free City College program in San Francisco, institutionTypeCovered, public community college]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: institutionTypeCovered Context triple: [Free City College program in San Francisco, institutionTypeCovered, public community college]
-
A.
coversInstitutionType
chosen
Indicates that one entity includes or applies to a particular type or category of institution.
-
B.
eligibleInstitution
Indicates that an institution satisfies specified criteria or requirements to qualify for a particular program, benefit, or status.
-
C.
organizationTypeServed
Indicates the type of organization that is served or supported by a given entity or activity.
-
D.
supportsInstitutionType
Indicates that one entity provides backing, resources, or endorsement specifically for a particular type or category of institution.
-
E.
institutionSpecialization
Indicates that an institution focuses on, is dedicated to, or has expertise in a particular field, domain, or area of activity.
- 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_69f224e3f6ac8190a13488516abca7c9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6a0ea04888190ac3a813b603bcb5c |
completed | May 3, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 29, 2026, 9:16 p.m.