Triple
T21781356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rina Indiastuti |
E537719
|
entity |
| Predicate | sharesAffiliationWith |
P72135
|
FINISHED |
| Object | academic staff of Universitas Padjadjaran |
—
|
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: academic staff of Universitas Padjadjaran | Statement: [Rina Indiastuti, sharesAffiliationWith, academic staff of Universitas Padjadjaran]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesAffiliationWith Context triple: [Rina Indiastuti, sharesAffiliationWith, academic staff of Universitas Padjadjaran]
-
A.
commonAffiliation
chosen
Indicates that two or more entities share the same organizational, institutional, or group affiliation.
-
B.
sharesNotableAssociationWith
Indicates a mutual, noteworthy connection or linkage between two entities that is significant enough to be recognized or highlighted.
-
C.
sharesColliderWith
Indicates that two entities are configured to use or occupy the same physics collider, causing them to share collision detection behavior.
-
D.
sharesAlignmentWith
Indicates that two entities have the same or sufficiently similar alignment, orientation, or stance according to a defined alignment system.
-
E.
sharesMotifsWith
Indicates that two entities contain or employ similar recurring themes, patterns, or symbolic elements.
- 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_69e0c470759c819094a215757113562b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0462db0208190ad31c132d3f875bc |
completed | April 28, 2026, 5:31 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:52 p.m.