Triple
T9392761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoss Cartwright (fictional character memorial) |
E226062
|
entity |
| Predicate | honorsCharacterType |
P60013
|
FINISHED |
| Object | supporting protagonist |
—
|
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: supporting protagonist | Statement: [Hoss Cartwright (fictional character memorial), honorsCharacterType, supporting protagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honorsCharacterType Context triple: [Hoss Cartwright (fictional character memorial), honorsCharacterType, supporting protagonist]
-
A.
honourType
Indicates the specific category or classification of an honour or award associated with an entity.
-
B.
honorsRole
Indicates that one entity formally recognizes and respects the position, title, or role held by another entity.
-
C.
typeOfCharacter
chosen
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
D.
honorsRoleAs
Indicates that one entity shows respect, recognition, or deference to another entity specifically in their official position or function.
-
E.
honorificType
Indicates the type or category of honorific or formal title associated with an entity in a given 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_69ca842f7e3481908bf5bcf52e032dbd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd510fec6481908b51c497744068c8 |
completed | April 1, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69cca545b2448190a4297312e39c21ac |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:45 p.m.