Triple
T27248587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universitas Pancasila |
E687419
|
entity |
| Predicate | hasCampusCultureBasedOn |
P181638
|
FINISHED |
| Object | Pancasila values |
—
|
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: Pancasila values | Statement: [Universitas Pancasila, hasCampusCultureBasedOn, Pancasila values]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampusCultureBasedOn Context triple: [Universitas Pancasila, hasCampusCultureBasedOn, Pancasila values]
-
A.
hasCampusOn
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
-
B.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
-
C.
hasCampusDominatingCommunity
Indicates that a particular community holds a dominant or leading presence or influence within a campus environment.
-
D.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
-
E.
isCampusFor
Indicates that a location serves as the campus associated with a particular institution or organization.
- F. None of above. chosen
Provenance (4 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_69ef35567e808190a94458cd44ebff0c |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f7805c25dc8190b9977c561ba15975 |
completed | May 3, 2026, 5:05 p.m. |
Created at: April 27, 2026, 10:43 a.m.