Triple
T7578331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guelph City Hall |
E179417
|
entity |
| Predicate | occupiesRole |
P11687
|
FINISHED |
| Object | seat of municipal government of Guelph |
—
|
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: seat of municipal government of Guelph | Statement: [Guelph City Hall, occupiesRole, seat of municipal government of Guelph]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupiesRole Context triple: [Guelph City Hall, occupiesRole, seat of municipal government of Guelph]
-
A.
servesRole
chosen
Indicates that one entity performs, fulfills, or occupies a particular function, position, or responsibility in relation to another entity.
-
B.
hasOrganizationalRole
Indicates that an entity holds a specific role, position, or function within an organization.
-
C.
definesRole
Indicates that one entity specifies or establishes the role, function, or position of another entity within a given context.
-
D.
hasNotableRoleIn
Indicates that an entity holds a significant or noteworthy role or function within another entity, event, work, or context.
-
E.
hasCapitalRole
Indicates that an entity holds an official role, function, or status specifically associated with a capital city.
- 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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f97460a481909d61fba555567b66 |
completed | March 27, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e04c2c8190a889d928515d9b8e |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:51 p.m.