Triple
T24446185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | History of Franklin County, Massachusetts |
E616410
|
entity |
| Predicate | includesInstitutionHistory |
P64535
|
FINISHED |
| Object | Deerfield Academy |
—
|
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: Deerfield Academy | Statement: [History of Franklin County, Massachusetts, includesInstitutionHistory, Deerfield Academy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesInstitutionHistory Context triple: [History of Franklin County, Massachusetts, includesInstitutionHistory, Deerfield Academy]
-
A.
includesInstitution
Indicates that one entity contains, encompasses, or has as a member a particular institution.
-
B.
hasFormerInstitution
Indicates that an entity was previously affiliated with, employed by, or enrolled in a particular institution in the past.
-
C.
hasInstitutions
chosen
Indicates that one entity possesses, contains, or is associated with one or more institutions.
-
D.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
-
E.
hadInstitution
Indicates that an entity was affiliated with, operated within, or was served by a particular institution during some period of time.
- 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_69e2d7edca608190aafefc8877a1b4da |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29853a3ac81908bb5398539a44cd6 |
completed | April 29, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:17 a.m.