Triple
T8564083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaughn Taylor |
E202760
|
entity |
| Predicate | characteristicRoleTypes |
P59266
|
FINISHED |
| Object | mild-mannered professionals |
—
|
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: mild-mannered professionals | Statement: [Vaughn Taylor, characteristicRoleTypes, mild-mannered professionals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characteristicRoleTypes Context triple: [Vaughn Taylor, characteristicRoleTypes, mild-mannered professionals]
-
A.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
B.
roleCharacteristic
chosen
Indicates that a particular characteristic, quality, or attribute is associated with and helps define a given role or function.
-
C.
typeOfRole
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
D.
identificationRole
Indicates that an entity serves as an identifier or plays a role in uniquely distinguishing or recognizing another entity.
-
E.
roleOfPeopleOnIt
Indicates the specific roles or functions that people have in relation to a particular object, event, or context.
- 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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9d11274819099cc33a21a993a1f |
completed | March 31, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:20 p.m.