Triple
T37583707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UP Diliman University Council |
E935037
|
entity |
| Predicate | campusOfSystem |
P90168
|
FINISHED |
| Object | University of the Philippines |
—
|
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: University of the Philippines | Statement: [UP Diliman University Council, campusOfSystem, University of the Philippines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusOfSystem Context triple: [UP Diliman University Council, campusOfSystem, University of the Philippines]
-
A.
campusSystem
chosen
Indicates a relationship where an educational institution is part of, managed by, or operates within a particular campus system or network.
-
B.
campusName
Indicates the official name assigned to a particular campus.
-
C.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
D.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
E.
cityCampusServes
Indicates that a city campus provides services, resources, or support to a particular population, area, or 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_69f76ece61dc8190a0ab33f8d87d0a7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:17 p.m.