Triple
T785161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Holyoke College |
E16584
|
entity |
| Predicate | offersResidentialLife |
P16150
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mount Holyoke College, offersResidentialLife, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersResidentialLife Context triple: [Mount Holyoke College, offersResidentialLife, yes]
-
A.
residentialCampus
chosen
Indicates that an educational institution’s campus includes on-site housing where students live as part of the campus community.
-
B.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
C.
offersDegree
Indicates that an institution or program provides a specific academic degree as an available qualification.
-
D.
hasResidentialColleges
Indicates that an institution or organization includes one or more residential colleges as part of its structure or system.
-
E.
cityCampus
Indicates that a campus is located within or associated with a particular city.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a76b0d6c8190a09b1a0bd4a6eeec |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:38 p.m.