Triple
T2627752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgetown Visitation Academy |
E59159
|
entity |
| Predicate | campusFeatures |
P2465
|
FINISHED |
| Object | historic convent buildings |
—
|
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: historic convent buildings | Statement: [Georgetown Visitation Academy, campusFeatures, historic convent buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusFeatures Context triple: [Georgetown Visitation Academy, campusFeatures, historic convent buildings]
-
A.
featuresInstitution
Indicates that one entity includes, presents, or highlights an institution as a notable component or participant.
-
B.
hasCampusFeature
chosen
Indicates that a campus possesses or includes a specific physical or functional feature.
-
C.
campusFacility
Indicates that one entity is a facility that is located on or belongs to a particular campus.
-
D.
cityCampusServes
Indicates that a city campus provides services, resources, or support to a particular population, area, or institution.
-
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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.