Triple
T18026403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doc Boone |
E431262
|
entity |
| Predicate | helpsCharacterType |
P129505
|
FINISHED |
| Object | social outcasts |
—
|
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: social outcasts | Statement: [Doc Boone, helpsCharacterType, social outcasts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsCharacterType Context triple: [Doc Boone, helpsCharacterType, social outcasts]
-
A.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
B.
workCharacterType
Indicates that a work involves or features a character of a specified type or role.
-
C.
character3
Indicates a tertiary or additional character role associated with an entity, typically the third distinct character linked within a given context or work.
-
D.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
E.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c6a4208190846ed28681ba7daa |
completed | April 19, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:24 a.m.