Triple
T37583674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UP Diliman University Council |
E935037
|
entity |
| Predicate | includesMembersWithRank |
P84741
|
FINISHED |
| Object | assistant professor |
—
|
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: assistant professor | Statement: [UP Diliman University Council, includesMembersWithRank, assistant professor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesMembersWithRank Context triple: [UP Diliman University Council, includesMembersWithRank, assistant professor]
-
A.
containsRank
chosen
Indicates that one entity includes or encompasses another entity that has a specific rank or hierarchical level within it.
-
B.
includedMembersOf
Indicates that certain members or elements are contained within, or form part of, a specified group or collection.
-
C.
admitsMemberRank
Indicates that an organization or group accepts individuals holding a specified rank or status as eligible members.
-
D.
includeMember
Indicates that one entity contains or has another entity as a member or part of its composition.
-
E.
eligibleMembers
Indicates that certain entities meet the required criteria or conditions to be considered eligible members of a specified group or category.
- 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_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.