Triple
T2449918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of the Philippines |
E53677
|
entity |
| Predicate | chancellorAtMainCampus |
P325
|
FINISHED |
| Object | Chancellor of UP Diliman |
—
|
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: Chancellor of UP Diliman | Statement: [University of the Philippines, chancellorAtMainCampus, Chancellor of UP Diliman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chancellorAtMainCampus Context triple: [University of the Philippines, chancellorAtMainCampus, Chancellor of UP Diliman]
-
A.
principalAndViceChancellor
Indicates that one entity holds the role of principal while also serving as the vice chancellor of an institution in relation to another entity.
-
B.
hasViceChancellor
Indicates that one entity serves as the vice chancellor of another entity.
-
C.
chancellorTitle
Indicates the official title or designation held by an individual serving in the role of chancellor.
-
D.
rectorOrPresident
Indicates that one entity serves as the rector or president (i.e., the chief executive or head) of another entity, typically an institution such as a university.
-
E.
hasChancellor
chosen
Indicates that an entity holds the position or role of chancellor for another entity.
- 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_69ab495d227c8190b26ae6548eeb1019 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0aed2688190a18fe66b98d80e0b |
completed | March 7, 2026, 7:15 a.m. |
Created at: March 6, 2026, 9:43 p.m.