Triple
T7328523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pauli Murray College |
E168936
|
entity |
| Predicate | universityResidentialCollegeNumber |
P28501
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Pauli Murray College, universityResidentialCollegeNumber, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: universityResidentialCollegeNumber Context triple: [Pauli Murray College, universityResidentialCollegeNumber, 13]
-
A.
numberOfResidentialColleges
chosen
Indicates the quantity of residential colleges associated with a given entity.
-
B.
hasResidentialColleges
Indicates that an institution or organization includes one or more residential colleges as part of its structure or system.
-
C.
numberOfUniversities
Indicates the quantity of universities associated with a given entity.
-
D.
numberOfUniversitySeats
Indicates the total count of available seats or positions offered by a university in a given context.
-
E.
campusSize
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a879b88190bef0fb6cbae411ff |
completed | March 27, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69c6e77230048190b2c29ca6b3a65b8e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:03 p.m.