Triple
T9947257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Gzowski College |
E195233
|
entity |
| Predicate | hasSocialComponent |
P38895
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Peter Gzowski College, hasSocialComponent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSocialComponent Context triple: [Peter Gzowski College, hasSocialComponent, yes]
-
A.
hasSocialDimension
chosen
Indicates that the relationship, attribute, or phenomenon involves social aspects, interactions, or implications among individuals or groups.
-
B.
hasSocialService
Indicates that an entity provides, offers, or is associated with a social service to another entity or community.
-
C.
hasSocialEngagement
Indicates that an entity participates in or maintains some form of social interaction, activity, or relationship with others.
-
D.
hasSocialGroup
Indicates that an entity belongs to, is associated with, or participates in a particular social group or community.
-
E.
hasSocialPractice
Indicates that one entity engages in, follows, or is characterized by a particular social practice or customary pattern of social behavior.
- 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_69ca82e96a108190932bd1fc4acd73a0 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb657b35c81909448e93999f6e77c |
completed | April 2, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:45 p.m.