Triple
T8703859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Sweet |
E206596
|
entity |
| Predicate | roleInCUPS |
P84640
|
FINISHED |
| Object | creator |
—
|
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: creator | Statement: [Michael Sweet, roleInCUPS, creator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCUPS Context triple: [Michael Sweet, roleInCUPS, creator]
-
A.
roleWithCEP
Indicates that an entity holds a specific role or function that is associated with a defined Contextualized Event or Process (CEP).
-
B.
roleInOperation
Indicates that an entity holds a specific function, duty, or position within a particular operation or activity.
-
C.
unitRole
Indicates the functional role or purpose that a unit serves within a larger system or context.
-
D.
ClientRole
Indicates that an entity participates in a relationship or interaction specifically in the capacity of a client.
-
E.
roleInIntegration
Indicates the specific function or responsibility an entity has within a combined or coordinated system, process, or integration.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58fa0a208190a520e0e1f7faaea9 |
completed | March 31, 2026, 11:30 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc582412f48190ae819965bfb0e75d |
completed | March 31, 2026, 11:26 p.m. |
Created at: March 30, 2026, 6:34 p.m.