Triple
T33567425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princeton Township |
E859794
|
entity |
| Predicate | containedInstitution |
P3814
|
FINISHED |
| Object | Princeton University |
—
|
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: Princeton University | Statement: [Princeton Township, containedInstitution, Princeton University]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containedInstitution Context triple: [Princeton Township, containedInstitution, Princeton University]
-
A.
inInstitution
Indicates that an entity is located within, belongs to, or is formally associated with a particular institution.
-
B.
includesInstitution
chosen
Indicates that one entity contains, encompasses, or has as a member a particular institution.
-
C.
involvesInstitution
Indicates that an action, event, or relationship includes or is associated with an institution as a participating party.
-
D.
associatedInstitution
Indicates that an entity has a formal connection or affiliation with a particular institution.
-
E.
servesInstitution
Indicates that one entity provides services or functions in support of a particular institution.
- 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_69f3497c1d288190a844ea699914e038 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a002ae74da08190a4b47e0ff0f7f8fe |
completed | May 10, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_6a0029cc369c81909578e52c4a75ab18 |
completed | May 10, 2026, 6:46 a.m. |
Created at: May 1, 2026, 1:40 a.m.